A Side Channel Delay Analysis for Hardware Trojan Detection

dc.contributor.authorVakil, Ashkan
dc.date.accessioned2021-01-04T20:44:21Z
dc.date.available2021-01-04T20:44:21Z
dc.date.issued2020-10
dc.description.abstractThis research proposal introduces a learning assisted modeling technique for the purpose of Hardware Trojan detection. Our proposed model, unlike the prior art, does not require a Golden fabricated chip as a fingerprint to compare the side channel signals. Instead, by modeling the voltage drop and voltage noise pre-fabrication, and with training a Neural Network post-fabrication, our proposed technique can improve the timing model collected during timing closure and produces a Neural assisted Golden Timing Model (NGTM) for side channel delay-signal analysis. The Neural Network acts as a process tracking watchdog for correlating the static timing data (produced at design time) to the delay information obtained from clock frequency sweeping test. Proposed modeling technique enables Hardware Trojan detection close to 90% in the simulated scenarios.
dc.identifier.urihttps://hdl.handle.net/1920/11915
dc.language.isoen_US
dc.rightsAttribution-ShareAlike 3.0 United States
dc.rights.urihttps://creativecommons.org/licenses/by-sa/3.0/us/
dc.subjectComputer security
dc.subjectComputer trojan
dc.subjectSide Channel Analysis
dc.titleA Side Channel Delay Analysis for Hardware Trojan Detection
dc.typeTechnical Report

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