非线性硅光子puf的深度学习攻击研究

Iskandar Atakhodjaev, B. Bosworth, Brian C. Grubel, M. Kossey, J. Villalba, A. Cooper, N. Dehak, A. Foster, M. Foster
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引用次数: 6

摘要

我们证明了非线性硅光子物理不可克隆函数(puf)可以抵抗对抗性深度学习攻击。我们发现这种电阻的根源是硅光子PUF标记的光学非线性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of Deep Learning Attacks on Nonlinear Silicon Photonic PUFs
We demonstrate that nonlinear silicon photonic Physical Unclonable Functions (PUFs) are resistant to adversarial deep learning attacks. We find that this resistance is rooted in the optical nonlinearity of the silicon photonic PUF token.
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