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Autoscopy Jr.: Intrusion Detection for Embedded Control Systems
Jason O. Reeves
Dartmouth TR2011-704

Abstract: Securing embedded control systems within the power grid presents a unique challenge: on top of the resource restrictions inherent to these devices, SCADA systems must also accommodate strict timing requirements that are non-negotiable, and their massive scale greatly amplifies costs such as power consumption. These constraints make the conventional approach to host intrusion detection--namely, employing virtualization in some manner--too costly or impractical for embedded control systems within critical infrastructure. Instead, we take an in-kernel approach to system protection, building upon the Autoscopy system developed by Ashwin Ramaswamy that places probes on indirectly-called functions and uses them to monitor its host system for behavior characteristic of control-flow-altering malware, such as rootkits. In this thesis, we attempt to show that such a method would indeed be a viable method of protecting embedded control systems.

We first identify several issues with the original prototype, and present a new version of the program (dubbed Autoscopy Jr.) that uses trusted location lists to verify that control is coming from a known, trusted location inside our kernel. Although we encountered additional performance overhead when testing our new design, we developed a kernel profiler that allowed us to identify the probes responsible for this overhead and discard them, leaving us with a final probe list that generated less than 5% overhead on every one of our benchmark tests. Finally, we attempted to run Autoscopy Jr. on two specialized kernels (one with an optimized probing framework, and another with a hardening patch installed), finding that the former did not produce enough performance benefits to preclude using our profiler, and that the latter required a different method of scanning for indirect functions for Autoscopy Jr. to operate.

We argue that Autoscopy Jr. is indeed a feasible intrusion detection system for embedded control systems, as it can adapt easily to a variety of system architectures and allows us to intelligently balance security and performance on these critical devices.

Note: M.S. Thesis. Advisor: Sergey Bratus. Builds upon work done in TR2009-644. REVISED on 27 September 2011 to correct one of the citations in the references section.


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   Jason O. Reeves, "Autoscopy Jr.: Intrusion Detection for Embedded Control Systems." Dartmouth Computer Science Technical Report TR2011-704, August 2011.


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