Simulation based Evaluation of a Code Diversification Strategy

Periodic randomization of a computer program’s binary code is an attractive technique for defending against several classes of advanced threats. In this paper we describe a model of attacker-defender interaction in which the defender employs such a technique against an attacker who is actively constructing an exploit using Return Oriented Programming (ROP). In order to successfully build a working exploit, the attacker must guess the locations of several small chunks of program code (i.e., gadgets) in the defended program’s memory space. As the attacker continually guesses, the defender periodically rotates to a newly randomized variant of the program, effectively negating any gains the attacker made since the last rotation. Although randomization makes the attacker’s task more difficult, it also incurs a cost to the defender. As such, the defender’s goal is to find an acceptable balance between utility degradation (cost) and security (benefit). One way to measure these two competing factors is the total task latency introduced by both the attacker and any defensive measures taken to thwart him. We simulated a number of diversity strategies under various threat scenarios and present the measured impact on the defender’s task.