Combating dependence explosion in forensic analysis using alternative tag propagation semantics

We are witnessing a rapid escalation in targeted cyber-attacks called Advanced and Persistent Threats (APTs). Carried out by skilled adversaries, these attacks take place over extended time periods, and remain undetected for months. A common approach for retracing the attacker's steps is to start with one or more suspicious events from system logs, and perform a dependence analysis to uncover the rest of attacker's actions. The accuracy of this analysis suffers from the dependence explosion problem, which causes a very large number of benign events to be flagged as part of the attack. In this paper, we propose two novel techniques, tag attenuation and tag decay, to mitigate dependence explosion. Our techniques take advantage of common behaviors of benign processes, while providing a conservative treatment of processes and data with suspicious provenance. Our system, called Morse, is able to construct a compact scenario graph that summarizes attacker activity by sifting through millions of system events in a matter of seconds. Our experimental evaluation, carried out using data from two government-agency sponsored red team exercises, demonstrates that our techniques are (a) effective in identifying stealthy attack campaigns, (b) reduce the false alarm rates by more than an order of magnitude, and (c) yield compact scenario graphs that capture the vast majority of the attack, while leaving out benign background activity.