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硬件木马检测因同代变体而膨胀，研究发现

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇新研究论文探讨了协议效应对Trust-Hub系列中基于特征的硬件木马检测的影响。研究发现，当同代基准测试变体同时包含在训练和测试数据集中时，检测器可以通过利用先前的主机逻辑来获得膨胀的性能指标。这种效应在不同的机器学习模型中进行了测量，包括随机森林、XGBoost和逻辑回归，当主机系列从测试集中排除时，性能显著下降。研究人员建议，具有多个主机电路变体的基准测试应报告家族感知排除以及汇总分数，以提供对检测能力的更准确评估。 AI

影响 强调了硬件安全基准测试中模型性能可能被高估的问题，表明需要更严格的评估协议。

排序理由 关于AI/ML研究方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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硬件木马检测因同代变体而膨胀，研究发现

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关于AI/ML研究方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Hang Xiao, Chuhong Xu, Kainan Zhou, Gangzhen Qian, Lu Yi ·

    Protocol effects on feature-based hardware-Trojan detection across Trust-Hub families

    arXiv:2609.07199v1 Announce Type: cross Abstract: Trust-Hub reuses host circuits: several files differ mainly in the inserted Trojan. When gates from sibling variants enter both training and test folds, a detector can benefit from host logic it has already seen. We measure that e…

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