Empirical evaluation of multi-device profiling side-channel attacks

Side-channel analysis of cryptographic systems can allow for the recovery of secret information by an adversary even where the underlying algorithms have been shown to be provably secure. This is achieved by exploiting the unintentional leakages inherent in the underlying implementation of the algorithm in software or hardware. Within this field of research, a class of attacks known as profiling attacks, or more specifically as used here template attacks, have been shown to be extremely efficient at extracting secret keys. Template attacks assume a strong adversarial model, in that an attacker has an identical device with which to profile the power consumption of various operations. This can then be used to efficiently attack the target device. Inherent in this assumption is that the power consumption across the devices under test is somewhat similar. This central tenet of the attack is largely unexplored in the literature with the research community generally performing the profiling stage on the same device as being attacked. This is beneficial for evaluation or penetration testing as it is essentially the best case scenario for an attacker where the model built during the profiling stage matches exactly that of the target device, however it is not necessarily a reflection on how the attack will work in reality. In this work, a large scale evaluation of this assumption is performed, comparing the key recovery performance across 20 identical smart-cards when performing a profiling attack.