Differential Fault Analysis for Block Ciphers

Abstract

Differential Fault Analysis (DFA) exploits the differences between a correct and a faulty output of a cipher implementation to derive the secret parameters. All the current DFA techniques are tailored to the cipher being attacked and do not provide a general framework. We propose an automated general framework to assess the vulnerability of block ciphers against DFAs, providing a conservative analysis on the attacker capabilities and a practical lower bound on the attacker effort required to extract the secret-key. The proposed technique is based on dataflow analysis of software cipher implementations and has been implemented as a pass of the llvm compiler infrastructure. This work shows how the automated tool we developed is able to detect which and how many faults an attacker can exploit to recover the values of portions of the secret-key material employed by a standard block cipher, validating the effectiveness of our approach. The precise analysis provided by our tool allows to apply the computationally demanding fault attack countermeasures only to the vulnerable portions of the cipher.