Automated Derivation of Application-Aware Error and Attack Detectors

307 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.The key insight in this dissertation is that certain data in the program is more important than other data from a reliability or security point of view (we call this the critical data). Protecting only the critical data provides significant performance improvements while achieving high detection coverage. The technique derives error and attack detectors to detect corruptions of critical data at runtime using a combination of static and dynamic approaches. The derived detectors are validated using both experimental approaches and formal verification. The experimental approaches validate the detectors using random fault-injection and known security attacks. The formal approach considers the effect of all possible errors and attacks according to a given fault or threat model and finds the corner cases that escape detection. The detectors have also been implemented in reconfigurable hardware in the context of the Reliability and Security Engine (RSE) [1].U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD