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Data Science Driven Approaches to Malware Detection

Event Details

Data Science Driven Approaches to Malware Detection

Time: October 13, 2015 from 9am to 10am
Location: Online
Website or Map:
Event Type: dsc, webinar
Organized By: Bill Vorhies, Editorial Director -- Data Science Central
Latest Activity: Sep 15, 2015

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Event Description

Space is limited.

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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. 

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. 

Speaker: Anirudh Kondaveeti, Ph.D. and Principal Data Scientist -- Pivotal

Hosted by: Bill Vorhies, Editorial Director -- Data Science Central

Again, Space is limited so please register early:

Reserve your Webinar seat now


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