Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/155545
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dc.contributor.authorBao, Zhenzhenen_US
dc.contributor.authorDong, Xiaoyangen_US
dc.contributor.authorGuo, Jianen_US
dc.contributor.authorLi, Zhengen_US
dc.contributor.authorShi, Danpingen_US
dc.contributor.authorSun, Siweien_US
dc.contributor.authorWang, Xiaoyunen_US
dc.date.accessioned2022-03-04T05:29:54Z-
dc.date.available2022-03-04T05:29:54Z-
dc.date.issued2021-
dc.identifier.citationBao, Z., Dong, X., Guo, J., Li, Z., Shi, D., Sun, S. & Wang, X. (2021). Automatic search of Meet-in-the-Middle preimage attacks on AES-like hashing. Advances in Cryptology – EUROCRYPT 2021, LNCS 12696, 771-804. https://dx.doi.org/10.1007/978-3-030-77870-5_27en_US
dc.identifier.isbn9783030778699-
dc.identifier.urihttps://hdl.handle.net/10356/155545-
dc.description.abstractThe Meet-in-the-Middle (MITM) preimage attack is highly effective in breaking the preimage resistance of many hash functions, including but not limited to the full MD5, HAVAL, and Tiger, and reduced SHA-0/1/2. It was also shown to be a threat to hash functions built on block ciphers like AES by Sasaki in 2011. Recently, such attacks on AES hashing modes evolved from merely using the freedom of choosing the internal state to also exploiting the freedom of choosing the message state. However, detecting such attacks especially those evolved variants is difficult. In previous works, the search space of the configurations of such attacks is limited, such that manual analysis is practical, which results in sub-optimal solutions. In this paper, we remove artificial limitations in previous works, formulate the essential ideas of the construction of the attack in well-defined ways, and translate the problem of searching for the best attacks into optimization problems under constraints in Mixed-Integer-Linear-Programming (MILP) models. The MILP models capture a large solution space of valid attacks; and the objectives of the MILP models are attack configurations with the minimized computational complexity. With such MILP models and using the off-the-shelf solver, it is efficient to search for the best attacks exhaustively. As a result, we obtain the first attacks against the full (5-round) and an extended (5.5-round) version of Haraka-512 v2, and 8-round AES-128 hashing modes, as well as improved attacks covering more rounds of Haraka-256 v2 and other members of AES and Rijndael hashing modes.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.description.sponsorshipNanyang Technological Universityen_US
dc.language.isoenen_US
dc.relation020509-00001en_US
dc.relation04INS000397C230en_US
dc.relationRG18/19en_US
dc.relationRG91/20en_US
dc.relationMOE2019-T2-1-060en_US
dc.rights© 2021 International Association for Cryptologic Research. All rights reserved. This paper was published by Springer in Proceedings of Advances in Cryptology – EUROCRYPT 2021 and is made available with permission of International Association for Cryptologic Research.en_US
dc.subjectScience::Mathematics::Discrete mathematics::Cryptographyen_US
dc.titleAutomatic search of Meet-in-the-Middle preimage attacks on AES-like hashingen_US
dc.typeConference Paperen
dc.contributor.schoolSchool of Physical and Mathematical Sciencesen_US
dc.contributor.conferenceAdvances in Cryptology – EUROCRYPT 2021en_US
dc.identifier.doi10.1007/978-3-030-77870-5_27-
dc.description.versionAccepted versionen_US
dc.identifier.scopus2-s2.0-85111365237-
dc.identifier.volumeLNCS 12696en_US
dc.identifier.spage771en_US
dc.identifier.epage804en_US
dc.subject.keywordsAESen_US
dc.subject.keywordsMeet-in-the-Middleen_US
dc.citation.conferencelocationZagreb, Croatiaen_US
dc.description.acknowledgementThis research is partially supported by the National Natural Science Foundation of China (Grant No. 61802400, 62032014, 61772519, 61961146004), the National Key Research and Development Program of China (Grant No. 2018YFA0704701, 2018YFA0704704), the Chinese Major Program of National Cryptography Development Foundation (No. MMJJ20180101, MMJJ20180102), the Major Program of Guangdong Basic and Applied Research (Grant No. 2019B030302008); Nanyang Technological University in Singapore under Grant 04INS000397C230, Singapore’s Ministry of Education under Grants RG18/19, RG91/20, and MOE2019-T2-1-060; the Gopalakrishnan – NTU Presidential Postdoctoral Fellowship 2020.en_US
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