https://en.wikipedia.org/w/index.php?action=history&feed=atom&title=Network_detection_and_response Network detection and response - Revision history 2025-06-17T07:21:23Z Revision history for this page on the wiki MediaWiki 1.45.0-wmf.5 https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1276915261&oldid=prev Bibamad at 14:42, 21 February 2025 2025-02-21T14:42:18Z <p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 14:42, 21 February 2025</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 20:</td> <td colspan="2" class="diff-lineno">Line 20:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Major attacks like [[WannaCry]] in 2017 and the [[SolarWinds]] breach in 2020 highlighted the need for solutions like NDR. Traditional perimeter defenses and signature-based tools proved insufficient against modern threats.&lt;ref name=":2" /&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Major attacks like [[WannaCry]] in 2017 and the [[SolarWinds]] breach in 2020 highlighted the need for solutions like NDR. Traditional perimeter defenses and signature-based tools proved insufficient against modern threats.&lt;ref name=":2" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>== <del style="font-weight: bold; text-decoration: none;">AI</del> applications ==</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>== <ins style="font-weight: bold; text-decoration: none;">Artificial Intelligence</ins> applications ==</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The use of [[artificial intelligence]] in NDR tools is growing, as security teams explore AI's potential to enhance NDR capabilities. Key AI use cases for NDR include:&lt;ref name=":1"&gt;{{Cite web |last=Grady |first=John |title=How AI benefits network detection and response |url=https://www.techtarget.com/searchsecurity/opinion/How-AI-benefits-network-detection-and-response |access-date=2023-08-15 |website=TechTarget |language=en}}&lt;/ref&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The use of [[artificial intelligence]] in NDR tools is growing, as security teams explore AI's potential to enhance NDR capabilities. Key AI use cases for NDR include:&lt;ref name=":1"&gt;{{Cite web |last=Grady |first=John |title=How AI benefits network detection and response |url=https://www.techtarget.com/searchsecurity/opinion/How-AI-benefits-network-detection-and-response |access-date=2023-08-15 |website=TechTarget |language=en}}&lt;/ref&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> </table> Bibamad https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1276915155&oldid=prev Bibamad at 14:41, 21 February 2025 2025-02-21T14:41:17Z <p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 14:41, 21 February 2025</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 16:</td> <td colspan="2" class="diff-lineno">Line 16:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The origins of NDR trace back to [[network traffic analysis]] (NTA) solutions that emerged around 2019. NTA provided greater visibility into network activities to quickly identify and respond to potential threats.&lt;ref name=":2"&gt;{{Cite web |last=Wiens |first=Christian |date=2023-02-02 |title=A Comprehensive Guide to Network Detection &amp; Response (NDR) — What CIOs &amp; Security Analysts Should Know |url=https://securityboulevard.com/2023/02/a-comprehensive-guide-to-network-detection-response-ndr-what-cios-security-analysts-should-know/ |access-date=2023-08-15 |website=Security Boulevard |language=en-US}}&lt;/ref&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The origins of NDR trace back to [[network traffic analysis]] (NTA) solutions that emerged around 2019. NTA provided greater visibility into network activities to quickly identify and respond to potential threats.&lt;ref name=":2"&gt;{{Cite web |last=Wiens |first=Christian |date=2023-02-02 |title=A Comprehensive Guide to Network Detection &amp; Response (NDR) — What CIOs &amp; Security Analysts Should Know |url=https://securityboulevard.com/2023/02/a-comprehensive-guide-to-network-detection-response-ndr-what-cios-security-analysts-should-know/ |access-date=2023-08-15 |website=Security Boulevard |language=en-US}}&lt;/ref&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>By 2020, NTA adoption was growing for real-time threat detection. That year, a study found that 87% of organizations used NTA, with 43% considering it a "first line of defense<del style="font-weight: bold; text-decoration: none;">.</del>" The NTA market was valued at US$2.9 billion in 2022, and expected to reach US$8.5 billion by 2032. NTA evolved into NDR as a distinct product category. NDR combined detection capabilities with incident response workflows. This enabled detecting and reacting to threats across networks in real time.&lt;ref name=":2" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>By 2020, NTA adoption was growing for real-time threat detection. That year, a study found that 87% of organizations used NTA, with 43% considering it a "first line of defense"<ins style="font-weight: bold; text-decoration: none;">.</ins> The NTA market was valued at US$2.9 billion in 2022, and expected to reach US$8.5 billion by 2032. NTA evolved into NDR as a distinct product category. NDR combined detection capabilities with incident response workflows. This enabled detecting and reacting to threats across networks in real time.&lt;ref name=":2" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Major attacks like [[WannaCry]] in 2017 and the [[SolarWinds]] breach in 2020 highlighted the need for solutions like NDR. Traditional perimeter defenses and signature-based tools proved insufficient against modern threats.&lt;ref name=":2" /&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Major attacks like [[WannaCry]] in 2017 and the [[SolarWinds]] breach in 2020 highlighted the need for solutions like NDR. Traditional perimeter defenses and signature-based tools proved insufficient against modern threats.&lt;ref name=":2" /&gt;</div></td> </tr> </table> Bibamad https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1228714494&oldid=prev 71.11.5.2: copy edits, removed ce tag 2024-06-12T19:31:50Z <p>copy edits, removed ce tag</p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 19:31, 12 June 2024</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>{{Multiple issues|</div></td> <td colspan="2" class="diff-empty diff-side-added"></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>{{copy edit|date=May 2024}}</div></td> <td colspan="2" class="diff-empty diff-side-added"></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{notability|date=May 2024}}</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{notability|date=May 2024}}</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>}}</div></td> <td colspan="2" class="diff-empty diff-side-added"></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{short description|Threat monitoring technology}}</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{short description|Threat monitoring technology}}</div></td> </tr> <tr> <td colspan="2" class="diff-empty diff-side-deleted"></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Network detection and response (NDR)''' refers to a category of [[network security]] products that detect abnormal system [[Behavior|behaviors]] by continuously analyzing [[network traffic]]. NDR solutions apply [[behavioral analytics]] to inspect raw [[Packet analyzer|network packets]] and [[metadata]] for both internal (east-west) and external (north-south) network communications.&lt;ref name=":0"&gt;{{Cite web |last=Jonathan Nunez, Andrew Davies |date=20 July 2023 |title=Hype Cycle for Security Operations, 2023 |url=https://www.gartner.com/doc/reprints?id=1-2EIN4TVS&amp;ct=230721&amp;st=sb&amp;__hstc=45788219.57a590308de95e51d2f62b49fac710ef.1691078838873.1691078838873.1691078838873.1&amp;__hssc=45788219.1.1691078838873&amp;__hsfp=3812163218&amp;hsCtaTracking=51e2e4ef-078c-41c0-a8bf-673c4e38176a%7C2cb608e8-3bb2-41fb-96a8-b3d410ee1978 |access-date=2023-08-08 |website=www.gartner.com}}&lt;/ref&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Network detection and response (NDR)''' refers to a category of [[network security]] products that detect abnormal system [[Behavior|behaviors]] by continuously analyzing [[network traffic]]. NDR solutions apply [[behavioral analytics]] to inspect raw [[Packet analyzer|network packets]] and [[metadata]] for both internal (east-west) and external (north-south) network communications.&lt;ref name=":0"&gt;{{Cite web |last=Jonathan Nunez, Andrew Davies |date=20 July 2023 |title=Hype Cycle for Security Operations, 2023 |url=https://www.gartner.com/doc/reprints?id=1-2EIN4TVS&amp;ct=230721&amp;st=sb&amp;__hstc=45788219.57a590308de95e51d2f62b49fac710ef.1691078838873.1691078838873.1691078838873.1&amp;__hssc=45788219.1.1691078838873&amp;__hsfp=3812163218&amp;hsCtaTracking=51e2e4ef-078c-41c0-a8bf-673c4e38176a%7C2cb608e8-3bb2-41fb-96a8-b3d410ee1978 |access-date=2023-08-08 |website=www.gartner.com}}&lt;/ref&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td colspan="2" class="diff-lineno">Line 13:</td> <td colspan="2" class="diff-lineno">Line 11:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Deployment options include physical or virtual sensors. Sensors are typically out-of-band, positioned to monitor network flows without impacting performance. Cloud-based NDR options integrate with IaaS providers to gain visibility across hybrid environments. Ongoing tuning helps reduce false positives. NDR competes against broader platforms like [[SIEM]] and [[Extended detection and response|XDR]] for security budgets.&lt;ref name=":0" /&gt; NDR can be used to complement EDR's blind spot.&lt;ref name=":3" /&gt;&lt;ref&gt;{{Cite web |title=Change Is Coming to the Network Detection and Response (NDR) Market |url=https://www.darkreading.com/cyber-risk/change-is-coming-to-the-network-detection-and-response-ndr-market |access-date=2024-05-21 |website=www.darkreading.com |language=en}}&lt;/ref&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Deployment options include physical or virtual sensors. Sensors are typically out-of-band, positioned to monitor network flows without impacting performance. Cloud-based NDR options integrate with IaaS providers to gain visibility across hybrid environments. Ongoing tuning helps reduce false positives. NDR competes against broader platforms like [[SIEM]] and [[Extended detection and response|XDR]] for security budgets.&lt;ref name=":0" /&gt; NDR can be used to complement EDR's blind spot.&lt;ref name=":3" /&gt;&lt;ref&gt;{{Cite web |title=Change Is Coming to the Network Detection and Response (NDR) Market |url=https://www.darkreading.com/cyber-risk/change-is-coming-to-the-network-detection-and-response-ndr-market |access-date=2024-05-21 |website=www.darkreading.com |language=en}}&lt;/ref&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>Key capabilities offered by NDR solutions include<del style="font-weight: bold; text-decoration: none;">:</del> <del style="font-weight: bold; text-decoration: none;">Real</del>-time threat detection through continuous monitoring, <del style="font-weight: bold; text-decoration: none;">Rapid</del> incident response workflows to minimize damage, <del style="font-weight: bold; text-decoration: none;">Reduced</del> complexity versus managing multiple point solutions, <del style="font-weight: bold; text-decoration: none;">Improved</del> visibility for compliance and risk management, <del style="font-weight: bold; text-decoration: none;">Automated</del> detection and response, <del style="font-weight: bold; text-decoration: none;">Endpoint</del> and user behavior analytics, <del style="font-weight: bold; text-decoration: none;">Integration</del> with [[SIEM]] for centralized monitoring.&lt;ref name=":2" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>Key capabilities offered by NDR solutions include <ins style="font-weight: bold; text-decoration: none;">real</ins>-time threat detection through continuous monitoring, <ins style="font-weight: bold; text-decoration: none;">rapid</ins> incident response workflows to minimize damage, <ins style="font-weight: bold; text-decoration: none;">reduced</ins> complexity versus managing multiple point solutions, <ins style="font-weight: bold; text-decoration: none;">improved</ins> visibility for compliance and risk management, <ins style="font-weight: bold; text-decoration: none;">automated</ins> detection and response, <ins style="font-weight: bold; text-decoration: none;">endpoint</ins> and user behavior analytics, <ins style="font-weight: bold; text-decoration: none;">and integration</ins> with [[SIEM]] for centralized monitoring.&lt;ref name=":2" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==History==</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>==History==</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The origins of NDR trace back to [[network traffic analysis]] (NTA) solutions that emerged around 2019. NTA provided greater visibility into network activities to quickly identify and respond to potential threats.&lt;ref name=":2"&gt;{{Cite web |last=Wiens |first=Christian |date=2023-02-02 |title=A Comprehensive Guide to Network Detection &amp; Response (NDR) — What CIOs &amp; Security Analysts Should Know |url=https://securityboulevard.com/2023/02/a-comprehensive-guide-to-network-detection-response-ndr-what-cios-security-analysts-should-know/ |access-date=2023-08-15 |website=Security Boulevard |language=en-US}}&lt;/ref&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The origins of NDR trace back to [[network traffic analysis]] (NTA) solutions that emerged around 2019. NTA provided greater visibility into network activities to quickly identify and respond to potential threats.&lt;ref name=":2"&gt;{{Cite web |last=Wiens |first=Christian |date=2023-02-02 |title=A Comprehensive Guide to Network Detection &amp; Response (NDR) — What CIOs &amp; Security Analysts Should Know |url=https://securityboulevard.com/2023/02/a-comprehensive-guide-to-network-detection-response-ndr-what-cios-security-analysts-should-know/ |access-date=2023-08-15 |website=Security Boulevard |language=en-US}}&lt;/ref&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>By 2020, NTA adoption was growing for real-time threat detection. That year, a study found 87% of organizations used NTA, with 43% considering it a "first line of defense." The NTA market was valued at US$2.9 billion in 2022, and expected to reach US$8.5 billion by 2032. NTA evolved into NDR as a distinct product category. NDR combined detection capabilities with incident response workflows. This enabled detecting and reacting to threats across networks in real<del style="font-weight: bold; text-decoration: none;">-</del>time.&lt;ref name=":2" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>By 2020, NTA adoption was growing for real-time threat detection. That year, a study found<ins style="font-weight: bold; text-decoration: none;"> that</ins> 87% of organizations used NTA, with 43% considering it a "first line of defense." The NTA market was valued at US$2.9 billion in 2022, and expected to reach US$8.5 billion by 2032. NTA evolved into NDR as a distinct product category. NDR combined detection capabilities with incident response workflows. This enabled detecting and reacting to threats across networks in real<ins style="font-weight: bold; text-decoration: none;"> </ins>time.&lt;ref name=":2" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Major attacks like [[WannaCry]] in 2017 and the [[SolarWinds]] breach in 2020 highlighted the need for solutions like NDR. Traditional perimeter defenses and signature-based tools proved insufficient against modern threats.&lt;ref name=":2" /&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Major attacks like [[WannaCry]] in 2017 and the [[SolarWinds]] breach in 2020 highlighted the need for solutions like NDR. Traditional perimeter defenses and signature-based tools proved insufficient against modern threats.&lt;ref name=":2" /&gt;</div></td> </tr> <tr> <td colspan="2" class="diff-lineno">Line 25:</td> <td colspan="2" class="diff-lineno">Line 23:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The use of [[artificial intelligence]] in NDR tools is growing, as security teams explore AI's potential to enhance NDR capabilities. Key AI use cases for NDR include:&lt;ref name=":1"&gt;{{Cite web |last=Grady |first=John |title=How AI benefits network detection and response |url=https://www.techtarget.com/searchsecurity/opinion/How-AI-benefits-network-detection-and-response |access-date=2023-08-15 |website=TechTarget |language=en}}&lt;/ref&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The use of [[artificial intelligence]] in NDR tools is growing, as security teams explore AI's potential to enhance NDR capabilities. Key AI use cases for NDR include:&lt;ref name=":1"&gt;{{Cite web |last=Grady |first=John |title=How AI benefits network detection and response |url=https://www.techtarget.com/searchsecurity/opinion/How-AI-benefits-network-detection-and-response |access-date=2023-08-15 |website=TechTarget |language=en}}&lt;/ref&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Improved threat detection<del style="font-weight: bold; text-decoration: none;"> </del>: AI can analyze large volumes of data on vulnerabilities, threats, and attack tactics to identify anomalous network activities. This allows NDR to detect emerging attack patterns with greater accuracy and fewer [[False positives and false negatives|false positives]].&lt;ref name=":1" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Improved threat detection: AI can analyze large volumes of data on vulnerabilities, threats, and attack tactics to identify anomalous network activities. This allows NDR to detect emerging attack patterns with greater accuracy and fewer [[False positives and false negatives|false positives]].&lt;ref name=":1" /&gt;</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Alert prioritization<del style="font-weight: bold; text-decoration: none;"> </del>: AI models can evaluate the criticality of NDR alerts based on factors like affected assets, exploitability, and potential impact. This enables security teams to triage alerts effectively despite staff shortages.&lt;ref name=":1" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Alert prioritization: AI models can evaluate the criticality of NDR alerts based on factors like affected assets, exploitability, and potential impact. This enables security teams to triage alerts effectively despite staff shortages.&lt;ref name=":1" /&gt;</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Analyst workflow optimization<del style="font-weight: bold; text-decoration: none;"> </del>: AI assistants can <del style="font-weight: bold; text-decoration: none;">provide guidance to</del> analysts during incident response, suggesting relevant investigation steps based on details of the threat. This amplifies analyst efficiency, especially for junior staff lacking specialized expertise.&lt;ref name=":1" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Analyst workflow optimization: AI assistants can <ins style="font-weight: bold; text-decoration: none;">guide</ins> analysts during incident response, suggesting relevant investigation steps based on details of the threat. This amplifies analyst efficiency, especially for junior staff lacking specialized expertise.&lt;ref name=":1" /&gt;</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Automated response<del style="font-weight: bold; text-decoration: none;"> </del>: Although not yet widely adopted, AI could enable NDR platforms to autonomously execute containment measures like quarantining endpoints. AI would identify and recommend response actions for analyst approval.&lt;ref name=":1" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Automated response: Although not yet widely adopted, AI could enable NDR platforms to autonomously execute containment measures like quarantining endpoints. AI would identify and recommend response actions for analyst approval.&lt;ref name=":1" /&gt;</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>* Security team communications<del style="font-weight: bold; text-decoration: none;"> </del>: NDR vendors are exploring integrations with natural language AI to generate incident reports and metrics digestible for business leaders, not just technical security staff.&lt;ref name=":1" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>* Security team communications: NDR vendors are exploring integrations with natural language AI to generate incident reports and metrics digestible for business leaders, not just technical security staff.&lt;ref name=":1" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== NDR Vendors ==</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== NDR Vendors ==</div></td> </tr> </table> 71.11.5.2 https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1228449216&oldid=prev John.linkshadow: /* NDR Vendors */ 2024-06-11T08:38:53Z <p><span class="autocomment">NDR Vendors</span></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 08:38, 11 June 2024</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 32:</td> <td colspan="2" class="diff-lineno">Line 32:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== NDR Vendors ==</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== NDR Vendors ==</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>According to [[Gartner]], NDR vendors include [[Cisco]], Corelight, [[Darktrace]], [[ExtraHop Networks|ExtraHop]], [[Fortinet]], IronNet, MixMode, Plixer, [[Trend Micro]], Trellix, [[Vectra AI]].&lt;ref name=":0" /&gt; </div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>According to [[Gartner]], NDR vendors include [[Cisco]], Corelight, [[Darktrace]],<ins style="font-weight: bold; text-decoration: none;"> [https://www.linkshadow.com/ LinkShadow]</ins> [[ExtraHop Networks|ExtraHop]], [[Fortinet]], IronNet, MixMode, Plixer, [[Trend Micro]], Trellix, [[Vectra AI]].&lt;ref name=":0" /&gt; </div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== References ==</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== References ==</div></td> </tr> </table> John.linkshadow https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1226041332&oldid=prev WikiCleanerBot: v2.05b - Bot T20 CW#61 - Fix errors for CW project (Reference before punctuation) 2024-05-28T06:43:23Z <p>v2.05b - <a href="/wiki/User:WikiCleanerBot#T20" title="User:WikiCleanerBot">Bot T20 CW#61</a> - Fix errors for <a href="/wiki/Wikipedia:WCW" class="mw-redirect" title="Wikipedia:WCW">CW project</a> (Reference before punctuation)</p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 06:43, 28 May 2024</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 9:</td> <td colspan="2" class="diff-lineno">Line 9:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity such as [[ransomware]] or insider malicious activity. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on [[Signature based detection|signature-based threat detection]]. This allows NDR to spot weak signals and unknown threats from network traffic, like [[Network Lateral Movement|lateral movement]] or [[data exfiltration]].&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity such as [[ransomware]] or insider malicious activity. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on [[Signature based detection|signature-based threat detection]]. This allows NDR to spot weak signals and unknown threats from network traffic, like [[Network Lateral Movement|lateral movement]] or [[data exfiltration]].&lt;ref name=":0" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt;<del style="font-weight: bold; text-decoration: none;">.</del> The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms<ins style="font-weight: bold; text-decoration: none;">.</ins>&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt; The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Deployment options include physical or virtual sensors. Sensors are typically out-of-band, positioned to monitor network flows without impacting performance. Cloud-based NDR options integrate with IaaS providers to gain visibility across hybrid environments. Ongoing tuning helps reduce false positives. NDR competes against broader platforms like [[SIEM]] and [[Extended detection and response|XDR]] for security budgets.&lt;ref name=":0" /&gt; NDR can be used to complement EDR's blind spot.&lt;ref name=":3" /&gt;&lt;ref&gt;{{Cite web |title=Change Is Coming to the Network Detection and Response (NDR) Market |url=https://www.darkreading.com/cyber-risk/change-is-coming-to-the-network-detection-and-response-ndr-market |access-date=2024-05-21 |website=www.darkreading.com |language=en}}&lt;/ref&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Deployment options include physical or virtual sensors. Sensors are typically out-of-band, positioned to monitor network flows without impacting performance. Cloud-based NDR options integrate with IaaS providers to gain visibility across hybrid environments. Ongoing tuning helps reduce false positives. NDR competes against broader platforms like [[SIEM]] and [[Extended detection and response|XDR]] for security budgets.&lt;ref name=":0" /&gt; NDR can be used to complement EDR's blind spot.&lt;ref name=":3" /&gt;&lt;ref&gt;{{Cite web |title=Change Is Coming to the Network Detection and Response (NDR) Market |url=https://www.darkreading.com/cyber-risk/change-is-coming-to-the-network-detection-and-response-ndr-market |access-date=2024-05-21 |website=www.darkreading.com |language=en}}&lt;/ref&gt;</div></td> </tr> </table> WikiCleanerBot https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1224926248&oldid=prev Bibamad: /* Description */ 2024-05-21T09:37:17Z <p><span class="autocomment">Description</span></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:37, 21 May 2024</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 7:</td> <td colspan="2" class="diff-lineno">Line 7:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity such as [[ransomware]] or insider malicious activity. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on [[Signature based detection|signature-based threat detection]]. This allows NDR to spot weak signals and unknown threats from network traffic, like lateral movement or [[data exfiltration]].&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity such as [[ransomware]] or insider malicious activity. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on [[Signature based detection|signature-based threat detection]]. This allows NDR to spot weak signals and unknown threats from network traffic, like <ins style="font-weight: bold; text-decoration: none;">[[Network Lateral Movement|</ins>lateral movement<ins style="font-weight: bold; text-decoration: none;">]]</ins> or [[data exfiltration]].&lt;ref name=":0" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt;. The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt;. The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> </tr> </table> Bibamad https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1224925885&oldid=prev Bibamad at 09:33, 21 May 2024 2024-05-21T09:33:56Z <p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:33, 21 May 2024</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 7:</td> <td colspan="2" class="diff-lineno">Line 7:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity such as [[ransomware]] or insider malicious activity. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on [[Signature based detection|signature-based threat detection]]. This allows NDR to spot weak signals and unknown threats from network traffic, like lateral movement or data exfiltration.&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity such as [[ransomware]] or insider malicious activity. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on [[Signature based detection|signature-based threat detection]]. This allows NDR to spot weak signals and unknown threats from network traffic, like lateral movement or <ins style="font-weight: bold; text-decoration: none;">[[</ins>data exfiltration<ins style="font-weight: bold; text-decoration: none;">]]</ins>.&lt;ref name=":0" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt;. The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt;. The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> </tr> </table> Bibamad https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1224925809&oldid=prev Bibamad: /* Description */ 2024-05-21T09:32:54Z <p><span class="autocomment">Description</span></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:32, 21 May 2024</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 7:</td> <td colspan="2" class="diff-lineno">Line 7:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity such as [[ransomware]] or insider malicious activity. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on signature-based threat detection. This allows NDR to spot weak signals and unknown threats from network traffic, like lateral movement or data exfiltration.&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity such as [[ransomware]] or insider malicious activity. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on <ins style="font-weight: bold; text-decoration: none;">[[Signature based detection|</ins>signature-based threat detection<ins style="font-weight: bold; text-decoration: none;">]]</ins>. This allows NDR to spot weak signals and unknown threats from network traffic, like lateral movement or data exfiltration.&lt;ref name=":0" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt;. The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt;. The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> </tr> </table> Bibamad https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1224925781&oldid=prev Bibamad at 09:32, 21 May 2024 2024-05-21T09:32:31Z <p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:32, 21 May 2024</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 7:</td> <td colspan="2" class="diff-lineno">Line 7:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity<del style="font-weight: bold; text-decoration: none;">,</del> such as [[ransomware]]<del style="font-weight: bold; text-decoration: none;">,</del> <del style="font-weight: bold; text-decoration: none;">as</del> <del style="font-weight: bold; text-decoration: none;">well</del> <del style="font-weight: bold; text-decoration: none;">as insider</del> <del style="font-weight: bold; text-decoration: none;">attacks</del>. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on signature-based threat detection. This allows NDR to spot weak signals and unknown threats from network traffic, like lateral movement or data exfiltration.&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>NDR is delivered through a combination of [[Computer hardware|hardware]] and [[software]] sensors, along with a software or [[Software as a service|SaaS]] management console. Organizations use NDR to detect and contain malicious post-breach activity such as [[ransomware]] <ins style="font-weight: bold; text-decoration: none;">or</ins> <ins style="font-weight: bold; text-decoration: none;">insider</ins> <ins style="font-weight: bold; text-decoration: none;">malicious</ins> <ins style="font-weight: bold; text-decoration: none;">activity</ins>. NDR focuses on identifying abnormal behavior patterns and anomalies rather than relying solely on signature-based threat detection. This allows NDR to spot weak signals and unknown threats from network traffic, like lateral movement or data exfiltration.&lt;ref name=":0" /&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt;. The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>NDR provides visibility into network activities to identify anomalies using [[machine learning]] algorithms&lt;ref name=":3"&gt;{{Cite web |last=Maor |first=Etay |title=Council Post: EDR, XDR, MDR: Making Sense Of Threat Detection And Response Acronyms |url=https://www.forbes.com/sites/forbestechcouncil/2024/03/05/edr-xdr-mdr-making-sense-of-threat-detection-and-response-acronyms/ |access-date=2024-05-21 |website=Forbes |language=en}}&lt;/ref&gt;. The automated response capabilities can help reduce the workload for security teams. NDR also assists incident responders with threat hunting by supplying context and analysis.&lt;ref name=":0" /&gt;</div></td> </tr> </table> Bibamad https://en.wikipedia.org/w/index.php?title=Network_detection_and_response&diff=1224925595&oldid=prev Bibamad at 09:30, 21 May 2024 2024-05-21T09:30:29Z <p></p> <table style="background-color: #fff; color: #202122;" data-mw="interface"> <col class="diff-marker" /> <col class="diff-content" /> <col class="diff-marker" /> <col class="diff-content" /> <tr class="diff-title" lang="en"> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">← Previous revision</td> <td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:30, 21 May 2024</td> </tr><tr> <td colspan="2" class="diff-lineno">Line 4:</td> <td colspan="2" class="diff-lineno">Line 4:</td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}}</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}}</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{short description|Threat monitoring technology}}</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>{{short description|Threat monitoring technology}}</div></td> </tr> <tr> <td class="diff-marker" data-marker="−"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Network detection and response (NDR)''' refers to a category of [[network security]] products that detect abnormal system [[Behavior|behaviors]] by continuously analyzing network traffic. NDR solutions apply [[behavioral analytics]] to inspect raw [[Packet analyzer|network packets]] and [[metadata]] for both internal (east-west) and external (north-south) network communications.&lt;ref name=":0"&gt;{{Cite web |last=Jonathan Nunez, Andrew Davies |date=20 July 2023 |title=Hype Cycle for Security Operations, 2023 |url=https://www.gartner.com/doc/reprints?id=1-2EIN4TVS&amp;ct=230721&amp;st=sb&amp;__hstc=45788219.57a590308de95e51d2f62b49fac710ef.1691078838873.1691078838873.1691078838873.1&amp;__hssc=45788219.1.1691078838873&amp;__hsfp=3812163218&amp;hsCtaTracking=51e2e4ef-078c-41c0-a8bf-673c4e38176a%7C2cb608e8-3bb2-41fb-96a8-b3d410ee1978 |access-date=2023-08-08 |website=www.gartner.com}}&lt;/ref&gt;</div></td> <td class="diff-marker" data-marker="+"></td> <td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Network detection and response (NDR)''' refers to a category of [[network security]] products that detect abnormal system [[Behavior|behaviors]] by continuously analyzing <ins style="font-weight: bold; text-decoration: none;">[[</ins>network traffic<ins style="font-weight: bold; text-decoration: none;">]]</ins>. NDR solutions apply [[behavioral analytics]] to inspect raw [[Packet analyzer|network packets]] and [[metadata]] for both internal (east-west) and external (north-south) network communications.&lt;ref name=":0"&gt;{{Cite web |last=Jonathan Nunez, Andrew Davies |date=20 July 2023 |title=Hype Cycle for Security Operations, 2023 |url=https://www.gartner.com/doc/reprints?id=1-2EIN4TVS&amp;ct=230721&amp;st=sb&amp;__hstc=45788219.57a590308de95e51d2f62b49fac710ef.1691078838873.1691078838873.1691078838873.1&amp;__hssc=45788219.1.1691078838873&amp;__hsfp=3812163218&amp;hsCtaTracking=51e2e4ef-078c-41c0-a8bf-673c4e38176a%7C2cb608e8-3bb2-41fb-96a8-b3d410ee1978 |access-date=2023-08-08 |website=www.gartner.com}}&lt;/ref&gt;</div></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br /></td> </tr> <tr> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> <td class="diff-marker"></td> <td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Description ==</div></td> </tr> </table> Bibamad