Date of Award


Document Type

Thesis (Master's)


Department of Computer Science

First Advisor

Sergey Bratus


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.


Originally posted in the Dartmouth College Computer Science Technical Report Series, number TR2011-704.