Abstract
Aiming at the implement of RSA algorithm, the attack methods are variety. In order to ensure the algorithm can against the side channel attack, in this paper, we present a masking scheme for RSA decryption. Our scheme exploits the multiply-homomorphic property of the existing RSA encryption scheme to compute an multiply-mask as an encryption of a random message and randomly splits the secret key into two shares as the sub-calculate such that each share is statistically independent from the original value. Our solution differs in several aspects from the recent masking RSA implementation. According to encrypted random number, the original ciphertext is blinded and the splitting secret key can reduce the size of the key and speed up the calculation of the algorithm. During the decryption, all the operations are under the masking state, therefore, through multiply masking and secret key splitting, we can secure a RSA implementation, the scheme we proposed can against the timing attack, simple power attack and differential power attack. Compared with others, this scheme can reach a higher calculation and security level.
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Acknowledgment
This work was supported by the National Natural Science Foundation of China (No. 61370188); The Scientific Research Common Program of Beijing Municipal Commission of Education (Nos. KM201610015002, KM201510015009); “13th Five-Year” National Cryptography Development Foundation (No. 20170110); The Beijing City Board of Education Science and technology key project (Nos. KZ201510015015, KZ201710015010); Project of Beijing Municipal College Improvement Plan (No. PXM2017_014223_000063); 2018 Academic innovation team of digital copyright protection (No. 041901180021093); BIGC Project (Nos. Ec201803, Ed201802, Ea201806).
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Zhang, J., Li, Z., Sun, Y., Liu, B., Yang, Y. (2018). A Homomorphic Masking Defense Scheme Based on RSA Cryptography Algorithm. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11065. Springer, Cham. https://doi.org/10.1007/978-3-030-00012-7_36
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