mlsanityData to 7 Oct 2026

OAT: Attesting Operation Integrity of Embedded Devices

arXiv 1802.03462 ↗First posted 9 Feb 2018cs.CRcited by 3

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Abstract (arXiv)

Due to the wide adoption of IoT/CPS systems, embedded devices(IoT frontends) become increasingly connected and mission-critical, which in turn has attracted advanced attacks (e.g., control-flow hijacks and data-only attacks). Unfortunately, IoT backends are unable to detect if such attacks have happened while receiving data, service requests, or operation status from IoT devices. As a result, currently, IoT backends are forced to blindly trust the IoT devices that they interact with. To fill this void, we first formulate a new security property for embedded devices, called "Operation Execution Integrity" or OEI. We then design and build a system, OAT, that enables remote OEI attestation for ARM-based bare-metal embedded devices. Our formulation of OEI captures the integrity of both control flow and critical data involved in an operation execution. Therefore, satisfying OEI entails that an operation execution is free of unexpected control and data manipulations, which existing attestation methods cannot check. Our design of OAT strikes a balance between prover's constraints (embedded devices' limited computing power and storage) and verifier's requirements(complete verifiability and forensic assistance). OAT uses a new control-flow measurement scheme, which enables light-weight and space-efficient collection of measurements (97% space reduction from the trace-based approach). OAT performs the remote control-flow verification through abstract execution, which is fast and deterministic. OAT also features lightweight integrity checking for critical data (74% fewer instrumentation needed than previous work). Our security analysis shows that OAT allows remote verifiers or IoT backends to detect both control-flow hijacks and data-only attacks that affect the execution of operations on IoT devices. In our evaluation using real embedded programs, OAT incurs a runtime overhead of 2.7%.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Feb 2018.

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Citing papers per year: 2024: 1; 2025: 1; 2026: 1.

3 papers.