Protecting lightweight block cipher implementation in mobile big data computing

The Mobile Big Data Computing is a new evolution of computing technology in data communication and processing. The data generated from mobile devices can be used for optimization and personalization of mobile services and other profitable businesses. Mobile devices are usually with limited computing resources, thus the security measures are constrained. To solve this problem, lightweight block ciphers are usually adopted. However, due to the easily exposed environment, lightweight block ciphers are apt to suffer from differential power attack. To counteract this attack, Nikova et al. proposed a provably secure method, namely sharing, to protect the cipher's implementation. But the complexity of sharing method is so high, making this method not practical. To address this issue, in this paper, we propose a GPU-based approach of sharing a 4-bit S-box by automatic search. GPU is a promising acceleration hardware with powerful parallel computing. By analyzing the sharing method carefully, we devise an optimal approach, namely OptImp, that improves the performance massively. The experiment results show that the proposed approach can achieve up to 300 times faster than the original method. With our approach, the sharing method can be used to protect lightweight block ciphers in practice.