Physical attacks on block ciphers

Abstract

The security of a cryptosystem is often compromised, not from a theoretical point of view, but by the leakage caused by the physical implementation of the cryptographic algorithm. A new class of attacks, called physical attacks, has shown the capability to exploit the unintentional physical behaviors from the cryptographic device, which usually provide enough information to recover the secret keys. Dierent methods have been proposed for conducting the attacks. Two of the main focus of physical attacks are side-channel attacks and fault attacks. For side-channel attacks, the strongest cryptanalysis can be carried when the attacker can prole the targeted device. In proling based side-channel attacks, a model is constructed to characterize the leakage behavior from the device. Recently, machine learning algorithms have been proposed as alternatives for the classical proling based attacks. Machine learning and side-channel analysis are two dierent elds of study, however they are similar, in a sense that both are mostly dealing with the same problem (i.e., classication). For fault attacks, the aim of the attacker is to disrupt the execution of cryptographic algorithms. Based on the erroneous results, it is possible to gain some additional information regarding the secret key. Many methods can be used to force a fault to the device, however, laser fault injection is still considered as the preferred tools for injecting faults, due to its high precision and repeatability.