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ACM Program. Lang."],"published-print":{"date-parts":[[2024,1,2]]},"abstract":"<jats:p>\n            Differential cryptanalysis is a powerful algorithmic-level attack, playing a central role in evaluating the security of symmetric cryptographic primitives. In general, the resistance against differential cryptanalysis can be characterized by the maximum expected differential characteristic probability. In this paper, we present generic and extensible approaches based on mixed integer linear programming (MILP) to bound such probability. We design a high-level cryptography-specific language\n            <jats:sc>EasyBc<\/jats:sc>\n            tailored for block ciphers and provide various rigorous procedures as differential denotational semantics, to automate the generation of MILP from block ciphers written in\n            <jats:sc>EasyBc<\/jats:sc>\n            . We implement an open-sourced tool that provides support for fully automated resistance evaluation of block ciphers against differential cryptanalysis. The tool is extensively evaluated on 23 real-life cryptographic primitives including all the 10 finalists of the NIST lightweight cryptography standardization process. The experiments confirm the expressivity of\n            <jats:sc>EasyBc<\/jats:sc>\n            and show that the tool can effectively prove the resistance against differential cryptanalysis for all block ciphers under consideration.\n            <jats:sc>EasyBc<\/jats:sc>\n            makes resistance evaluation against differential cryptanalysis easily accessible to cryptographers.\n          <\/jats:p>","DOI":"10.1145\/3632871","type":"journal-article","created":{"date-parts":[[2024,1,5]],"date-time":"2024-01-05T20:48:51Z","timestamp":1704487731000},"page":"848-881","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["EasyBC: A Cryptography-Specific Language for Security Analysis of Block Ciphers against Differential Cryptanalysis"],"prefix":"10.1145","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-5840-0246","authenticated-orcid":false,"given":"Pu","family":"Sun","sequence":"first","affiliation":[{"name":"ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0581-2679","authenticated-orcid":false,"given":"Fu","family":"Song","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Beijing, China"},{"name":"University of Chinese Academy of Sciences, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2988-6012","authenticated-orcid":false,"given":"Yuqi","family":"Chen","sequence":"additional","affiliation":[{"name":"ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5993-1665","authenticated-orcid":false,"given":"Taolue","family":"Chen","sequence":"additional","affiliation":[{"name":"Birkbeck University of London, London, UK"}]}],"member":"320","published-online":{"date-parts":[[2024,1,5]]},"reference":[{"key":"e_1_3_1_2_1","doi-asserted-by":"publisher","unstructured":"Ahmed Abdelkhalek Yu Sasaki Yosuke Todo Mohamed Tolba and Amr M Youssef. 2017. 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