Microscope: Causality Inference Crossing the Hardware and Software Boundary from Hardware Perspective


연구 분야: Verification



학회: 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC)


초록

The increasing complexity of System-on-Chip (SoC) designs and the rise of third-party vendors in the semiconductor industry have led to unprecedented security concerns. Traditional formal methods struggle to address software-exploited hardware bugs, and existing solutions for hardware-software co-verification often fall short. This paper presents Microscope, a novel framework for inferring software instruction patterns that can trigger hardware vulnerabilities in SoC designs. Microscope enhances the Structural Causal Model (SCM) with hardware features, creating a scalable Hardware Structural Causal Model (HW-SCM). A domain-specific language (DSL) in SMT-LIB represents the HW-SCM and predefined security properties, with incremental SMT solving deducing possible instructions. Microscope identifies causality to determine whether a hardware threat could result from any software events, providing a valuable resource for patching hardware bugs and generating test input. Extensive experimentation demonstrates Microscope’s capability to infer the causality of a wide range of vulnerabilities and bugs located in SoC-level benchmarks.


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Zhaoxiang Liu

Kansas State University

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Kejun Chen

Kansas State University

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Dean Sullivan

University of New Hampshire

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📄 논문 정보

발행 연도 2024년
인용수 127
출판 국가 Andorra
사이트 IEEE
좋아요 수 0

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