{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/81855"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/81855","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Automated Derivation of Application-Aware Error and Attack Detectors","abstract":"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. 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