Advanced Encryption Standard Block Cipher Research Articles

Analyzing the Performance of the Advanced Encryption Standard Block Cipher Modes of Operation: Highlighting the National Institute of Standards and Technology Recommendations

When using a symmetric encryption algorithm, specifically the AES, the Block Cipher Mode of Operation to be used must be specified. Usually choosing the mode of operation is influenced by two main factors: 1. Security; and the 2. Performance of the mode. Most of the related literature explores the security of the modes. In contrast, this research paper explores, compares and evaluates the performance of the five modes of operation recommended by the National Institute of Standards and Technology (NIST). A code using Crypto++ cryptographic library has been developed to benchmark the performance of these modes. Based on the conducted experiments and obtained results, the Counter mode of operation has been found generally superior to the other four modes of operation in terms of performance especially when increasing the input size.

Improved algebraic side-channel attack on AES

In this paper, we present improvements of the algebraic side-channel analysis of the Advanced Encryption Standard (AES) proposed in the works of M. Renauld and F.-X. Standaert. In particular, we optimize the algebraic representation of both the AES block cipher and obtained side-channel information, in the form of Hamming weights of intermediate states, in order to speed up the attack and increase its success rate. We study the performance of our improved attack in both known and unknown plaintext/ciphertext attack scenarios. Our experiments indicate that in both cases the amount of required side-channel information is less than the one required in the attacks introduced earlier. Furthermore, we introduce a method for handling erroneous side-channel information, which allows our improved algebraic side-channel attack (IASCA) to partially escape the assumption of an error-free environment and thus become applicable in practice. We demonstrate the practical use of our IASCA by inserting predictions from a single-trace template attack.