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English(EN) ADVERSARIAL: And-Inverter Graph-Assisted Hardware Trojan Detection At Scale

新方法使用与非门图进行可扩展硬件木马检测

研究人员开发了一种新颖的方法,通过将大型片上系统(SoC)设计表示为与非门图(AIGs)来检测其中的硬件木马。该方法利用知识图嵌入来创建电路结构的紧凑、固定大小的表示,从而使复杂性能够与边数成线性扩展。该方法能够跨深度数据通路进行符号学习,以识别指示木马的罕见、不一致的连接,并在实验中展示了实际的可扩展性和木马与良性节点之间的清晰分离。 AI

排序理由 该集群包含一篇详细介绍新硬件安全方法的 ist 研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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新方法使用与非门图进行可扩展硬件木马检测

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该集群包含一篇详细介绍新硬件安全方法的 ist 研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Yaroslav Popryho, Debjit Pal, Inna Partin-Vaisband ·

    对抗性:大规模与非门图辅助硬件木马检测

    arXiv:2607.23882v1 Announce Type: new Abstract: Modern System-on-Chip (SoCs) often contain hundreds of millions to tens of billions of gates, making existing Hardware Trojan (HT) detection methods impractical due to their immense scale. The proposed approach incorporates symbolic…