Yueheng and Rajdeep’s talk explores the application of AI in detecting Attack Campaigns within a company’s cybersecurity infrastructure. These campaigns involve coordinated efforts by hackers to breach systems and steal data. Yueheng’s research centers on clustering low-level alert data to form higher-level clusters. The objective is to group together potential malicious alerts, distinguishing them from noise or benign alerts. Rajdeep then employs a Markov model to sequence these clusters into likely Attack Campaigns, each assigned a probability. Their goal is to equip cybersecurity analysts with tools to rapidly identify and combat such threats.
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