All Videos Tagged Malware Detection (Data Science Central) - Data Science Central 2020-07-12T14:17:39Z https://www.datasciencecentral.com/video/video/listTagged?tag=Malware+Detection&rss=yes&xn_auth=no DSC Webinar Series: Data Science Driven Approaches to Malware Detection tag:www.datasciencecentral.com,2015-10-13:6448529:Video:336014 2015-10-13T21:28:50.889Z Tim Matteson https://www.datasciencecentral.com/profile/2edcolrgc4o4b <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-data-science-driven-approaches-to-malware"><br /> <img alt="Thumbnail" height="180" src="https://storage.ning.com/topology/rest/1.0/file/get/2781532809?profile=original&amp;width=240&amp;height=180" width="240"></img><br /> </a> <br></br>Malware detection within enterprise networks is a critical component of an effective information security strategy. A "watering hole" attack is one example of how legitimate websites can be stealthily injected with malware. The malware lies undetected, while redirecting traffic from a legitimate site to a malicious site, which hosts an exploit… <a href="https://www.datasciencecentral.com/video/dsc-webinar-series-data-science-driven-approaches-to-malware"><br /> <img src="https://storage.ning.com/topology/rest/1.0/file/get/2781532809?profile=original&amp;width=240&amp;height=180" width="240" height="180" alt="Thumbnail" /><br /> </a><br />Malware detection within enterprise networks is a critical component of an effective information security strategy. A "watering hole" attack is one example of how legitimate websites can be stealthily injected with malware. The malware lies undetected, while redirecting traffic from a legitimate site to a malicious site, which hosts an exploit kit that can compromise users' machines. Instances of watering hole attacks are increasing rapidly -- making them especially important to detect.<br /> <br /> In this DSC webinar, one of Pivotal's principal data scientists will discuss data science driven approaches to finding domains that have time and user-based co-occurrence relationships. Developed to find low-support and high-confidence malicious domain associations, these methods aid in the detection of coordinated network intrusions, like watering hole attacks. The session will also demonstrate a scalable and operationalizable framework to detect domain associations by analyzing the web traffic of users in any organization.<br /> <br /> Speaker: Anirudh Kondaveeti, Ph.D. and Principal Data Scientist -- Pivotal<br /> <br /> Hosted by: Bill Vorhies, Editorial Director -- Data Science Central