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Field-programmable gate arrays (FPGAs) are widely used in cloud servers as an acceleration solution for compute-intensive tasks. Cloud FPGAs are typically multi-tenant, enabling resource sharing among multiple users but are vulnerable to power side-channel analysis (SCA) attacks due to their programmability and runtime dynamic reconfigurability. It is well-known that the clock frequencies of the circuits on multi-tenant FPGAs affect power consumption, but their impact on remote correlation power analysis (CPA) attacks has largely been ignored in the literature. This work systematically evaluates how clock frequency variations influence the effectiveness of remote CPA attacks on multi-tenant FPGAs. We develop a theoretical model to quantify this impact and validate our findings through the CPA attacks on processors running AES-128 and SM4 cryptographic algorithms. Our results demonstrate that the runtime clock frequency significantly affects the performance of remote CPA attacks. Our work provides valuable insights into the security implications of frequency scaling in multi-tenant FPGAs and offers guidance on selecting clock frequencies to mitigate power side-channel risks.
