Physical unclonable functions provide a unique 'fingerprint' to a physical entity by exploiting the inherent physical randomness. With the help of quantum information theory, this paper proposes solutions to protect PUFs against machine learning-based attacks. Here, based on the querying capability, we first divide the adversaries into two classes, namely adaptive and weak adversaries. We also modify an existing security notion, universal unforgeability, to capture the power of those two classes of adversaries. We then introduce the notion of a hybrid PUF, using a classical PUF and quantum conjugate coding. This construction encodes the output of a classical PUF in non-orthogonal quantum states. We show that the indistinguishability of those states can significantly enhance the security of the classical PUFs against weak adversaries. Moreover, we show that learning the underlying classical PUF from the outputs of our HPUF construction is at least as hard as learning the classical PUF from its random noisy outputs. To prevent the adversaries from querying the PUFs adaptively, we borrow ideas from a classical lockdown technique and apply them to our hybrid PUF. We show that the hybrid PUFs, together with the lockdown technique, termed as hybrid locked PUF, can provide a secure client authentication protocol against adaptive adversaries and are implementable with the current day quantum communication technology. Moreover, we show that HLPUF allows the server to reuse the challenges for further client authentication, providing an efficient solution for running a PUF-based client authentication protocol for a longer period while maintaining a small-sized challenge-response pairs database on the server-side. Finally, we explore the lockdown technique with quantum PUF and show that the direct adaptation of the classical lockdown technique will not work with the fully quantum PUFs.
翻译:物理上不可调试的功能为物理实体提供了一个独特的“ 指针” 概念, 利用内在的物理随机性编码。 在量子信息理论的帮助下, 本文提出了保护PUF不受机器学习攻击的解决方案。 在这里, 根据质询能力, 我们首先将对手分为两大类, 即适应性和弱对手。 我们还修改了一个现有的安全概念, 普遍的不可调试性, 以捕捉这两类对手的力量。 然后我们引入了混合PUF的概念, 使用古典的 PUF 和量子同级的调试编码。 这个建筑将古典PUF的输出编码成一个代码, 在非量子信息学国家里, 保护古典PUF的输出。 我们显示这些国家的不可分化性能可以大大加强古典PUFP的可靠性, 并且我们用固定的量值客户机里, 将一个固定的量值的量值数据库 展示一个固定的量值 。