显微镜:从硬件角度看跨越硬件和软件界限的因果推理

Zhaoxiang Liu, Kejun Chen, Dean Sullivan, Orlando Arias, R. Dutta, Yier Jin, Xiaolong Guo
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引用次数: 0

摘要

系统级芯片(SoC)设计的复杂性不断增加以及半导体行业第三方供应商的崛起,引发了前所未有的安全问题。传统的形式化方法难以解决被软件利用的硬件漏洞,而现有的软硬件协同验证解决方案也往往不尽如人意。本文介绍的 Microscope 是一种新型框架,用于推断 SoC 设计中可能触发硬件漏洞的软件指令模式。Microscope 利用硬件特性增强了结构因果模型(SCM),创建了可扩展的硬件结构因果模型(HW-SCM)。SMT-LIB 中的特定领域语言 (DSL) 表示 HW-SCM 和预定义的安全属性,并通过增量 SMT 解算推导出可能的指令。Microscope 可识别因果关系,确定硬件威胁是否可能源于任何软件事件,为修补硬件漏洞和生成测试输入提供了宝贵的资源。大量实验证明,Microscope 能够推断出 SoC 级基准中各种漏洞和错误的因果关系。
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Microscope: Causality Inference Crossing the Hardware and Software Boundary from Hardware Perspective
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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