A Survey of Machine Learning Defense and Attack of Physical Unclonable Function
With the development of satellite navigation technology,navigation products such as chips,modules,and boards are widely used in various navigation terminal devices.However,the communication security issues of these devices in open environments are increasingly prominent.Physical Unclonable Function(PUF)is a new type of"hardware fingerprint"technology.PUF based identity authentication can provide hardware-level authentication for devices,meeting their lightweight and high-security authentication requirements.To solve the problem of the vulnerability of most PUF structures to Machine Learning(ML)modeling attacks,different structure improvement methods are introduced,the characteristics of several commonly used ML attack algorithms are analyzed,the performance evaluation methods for both defense and attack are proposed,and the future development trend from the aspect of security is discussed.
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