Effectiveness of defenses against profiling side-channel attacks Public
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Side-channel attacks are commonly used to extract cryptographic keys from embedded systems. We study side-channel countermeasures originally designed to protect against differential power analysis (DPA) and determine how effective they are against profiling attacks using neural networks. We compiled two otherwise identical binaries that perform AES-256 encryption, one with DPA protections and one without. In our experiments, the binary with the countermeasures required 8 to 18 times as much attack data as the unprotected binary to achieve the same efficacy of attack, given the same amount of training data for both binaries. We conclude that our DPA protections may make profiling attacks time prohibitive in some cases but they are insufficient to completely defend against profiling attacks.
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