Automated Discovery of Mimicry Attacks
WISCONSIN UNIV-MADISON DEPT OF COMPUTER SCIENCES
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Model-based anomaly detection systems restrict program execution by a predefined model of allowed system call sequences. These systems are useful only if they detect actual attacks. Previous research developed manually-constructed mimicry and evasion attacks that avoided detection by hiding a malicious series of system calls within a valid sequence allowed by the model. Our work helps to automate the discovery of such attacks. We start with two models a program model of the applications system call behavior and a model of security-critical operating system state. Given unsafe OS state configurations that describe the goals of an attack, we then find system call sequences allowed as valid execution by the program model that produce the unsafe configurations. Our experiments show that we can automatically find attack sequences in models of programs such as wu-ftpd and passwd that previously have only been discovered manually. When undetected attacks are present, we frequently find the sequences with less than 2 seconds of computation.
- Operations Research
- Computer Systems Management and Standards