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http://dx.doi.org/10.13089/JKIISC.2022.32.6.1045

Non-Profiling Analysis Attacks on PQC Standardization Algorithm CRYSTALS-KYBER and Countermeasures  

Jang, Sechang (Hoseo University)
Ha, Jaecheol (Hoseo University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.32, no.6, 2022 , pp. 1045-1057 More about this Journal
Abstract
Recently, the National Institute of Standards and Technology (NIST) announced four cryptographic algorithms as a standard candidates of Post-Quantum Cryptography (PQC). In this paper, we show that private key can be exposed by a non-profiling-based power analysis attack such as Correlation Power Analysis (CPA) and Differential Deep Learning Analysis (DDLA) on CRYSTALS-KYBER algorithm, which is decided as a standard in the PKE/KEM field. As a result of experiments, it was successful in recovering the linear polynomial coefficient of the private key. Furthermore, the private key can be sufficiently recovered with a 13.0 Normalized Maximum Margin (NMM) value when Hamming Weight of intermediate values is used as a label in DDLA. In addition, these non-profiling attacks can be prevented by applying countermeasures that randomly divides the ciphertext during the decryption process and randomizes the starting point of the coefficient-wise multiplication operation.
Keywords
Post-Quantum Cryptography; CRYSTALS-KYBER; Power Analysis Attack; Deep Learning Analysis attack;
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Times Cited By KSCI : 1  (Citation Analysis)
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