Biblio

There are various Lightweight Block Ciphers (LBC) nowadays that exist to meet the demand on security requirements of the current trend in computing world, the application in the resource-constrained devices, and the Internet of Things (IoT) technologies. One way to evaluate these LBCs is to conduct a performance analysis. Performance evaluation parameters seek appropriate value such as encryption time, security level, scalability, and flexibility. Like SIMECK block cipher whose algorithm design was anchored with the SIMON and SPECK block ciphers were efficient in security and performance, there is a need to revisit its design. This paper aims to present a comparative study on the performance analysis of the enhanced round function of the SIMECK Family block cipher. The enhanced ARX structure of the round function on the three variants shows an efficient performance over the original algorithm in different simulations using the following methods of measurement; avalanche effect, runtime performance, and brute-force attack. Its recommended that the enhanced round function of the SIMECK family be evaluated by different security measurements and attacks.

Energy efficiency and security is a critical requirement for computing at edge nodes. Unrolled architectures for lightweight cryptographic algorithms have been shown to be energy-efficient, providing higher performance while meeting resource constraints. Hardware implementations of unrolled datapaths have also been shown to be resistant to side channel analysis (SCA) attacks due to a reduction in signal-to-noise ratio (SNR) and an increased complexity in the leakage model. This paper demonstrates optimal leakage models and an improved CFA attack which makes it feasible to extract first-order side-channel leakages from combinational logic in the initial rounds of unrolled datapaths. Several leakage models, targeting initial rounds, are explored and 1-bit hamming weight (HW) based leakage model is shown to be an optimal choice. Additionally, multi-band narrow bandpass filtering techniques in conjunction with correlation frequency analysis (CFA) is demonstrated to improve SNR by up to 4×, attributed to the removal of the misalignment effect in combinational logics and signal isolation. The improved CFA attack is performed on side channel signatures acquired for 7-round unrolled SIMON datapaths, implemented on Sakura-G (XILINX spartan 6, 45nm) based FPGA platform and a 24× reduction in minimum-traces-to-disclose (MTD) for revealing 80% of the key bits is demonstrated with respect to conventional time domain correlation power analysis (CPA). Finally, the proposed method is successfully applied to a fully-unrolled datapath for PRINCE and a parallel round-based datapath for Advanced Encryption Standard (AES) algorithm to demonstrate its general applicability.