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• W2396444304 abstract "This paper proposes the use of Cellular Non-Linear Networks (CNNs) as physical uncloneablefunctions (PUFs). We argue that analog circuits o®er higher security than existing digital PUFsand that the CNN paradigm allows us to build large, unclonable, and scalable analog PUFs, whichstill show a stable and repeatable input output behavior.CNNs are dynamical arrays of locally-interconected cells, with a cell dynamics that dependsupon the interconnection strengths to their neighbors. They can be designed to evolve in timeaccording to partial di®erential equations. If this equation describes a physical phenomenon, thenthe CNN can simulate a complex physical system on-chip. This can be exploited to create electricalPUFs with high relevant structural information content.To illustrate our paradigm at work, we design a circuit that directly emulates nonlinear wavepropagation phenomena in a random media. It e®ectively translates the complexity of optical PUFsinto electrical circuits." @default.
• W2396444304 created "2016-06-24" @default.
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• W2396444304 date "2009-01-01" @default.
• W2396444304 modified "2023-09-23" @default.
• W2396444304 title "On-Chip Electric Waves: An Analog Circuit Approach to Physical Uncloneable Functions" @default.
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