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Improving Performance in Space-Hard Algorithms

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Cyber Security, Cryptology, and Machine Learning (CSCML 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13914))

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Abstract

Protecting secret keys from malicious observers is a major problem for cryptographic algorithms in untrusted environments. White-box cryptography suggests hiding the key in the cipher code with an appropriate method such that extraction of the key becomes impossible in the white-box settings. The key is generally embedded into the confusion layer with suitable methods. One of them is using encoding techniques. Nevertheless, many encoding methods are vulnerable to algebraic attacks and side-channel analysis. Another is the space hardness concept, which creates large lookup tables that cannot be easily extracted from the device. In (M,Z)-space hard algorithms, the secret key is embedded in large tables created as a substitution box with a suitable block cipher. So the key extraction problem in the white-box settings turns into a key recovery problem in the black-box case. One of the main issues in (M,Z)-space hard algorithms is accelerating the run-time of the black-box/white-box implementation. In this study, we aim to use the advantage of the efficiency of lightweight components to speed up the diffusion layer of white-box algorithms without decreasing the security size. Therefore, we compare the linear components of NIST Lightweight Standardization candidates for efficiency and suitability to white-box settings in existing space hard ciphers. The performance results of the algorithms are compared with WARX and SPNbox-32. According to the results, using the lightweight components in the diffusion layer accelerates the performance of white-box algorithms by at least nine times.

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Correspondence to Hatice Kübra Güner .

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Güner, H.K., Mangır, C., Yayla, O. (2023). Improving Performance in Space-Hard Algorithms. In: Dolev, S., Gudes, E., Paillier, P. (eds) Cyber Security, Cryptology, and Machine Learning. CSCML 2023. Lecture Notes in Computer Science, vol 13914. Springer, Cham. https://doi.org/10.1007/978-3-031-34671-2_28

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  • DOI: https://doi.org/10.1007/978-3-031-34671-2_28

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