WEBINAR: Data Science Driven Approaches to Malware Detection - 13 October 2015

Overview

Title: Data Science Driven Approaches to Malware Detection

Date: Tuesday, October 13, 2015

Time: 09:00 AM Pacific Daylight Time

Duration: 1 hour

Summary

Data Science Driven Approaches to Malware Detection

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 operationalisable framework to detect domain associations by analysing 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

Register here