{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T01:26:20Z","timestamp":1769563580315,"version":"3.49.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686448","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T00:00:00Z","timestamp":1769472000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,27]]},"abstract":"<jats:p>Permutation is a commonly used operation in image encryption schemes. Many schemes adopt a separate row and column permutation to increase the encryption efficiency while ignoring the security. This paper proposes an efficient known-plaintext attack (KPA) for row-column-based permutation. A special ID method based on the Pearson correlation coefficient is proposed to label each column or row. Only one pair of known plaintext-ciphertext images is enough to determine the permutation rules completely. With this attack method for permutation, a classic permutation-then-XOR image encryption scheme is broken with only two known plaintext-ciphertext image pairs. A numerical example of the proposed attack is provided to show the process intuitively and clearly. In addition, the cryptanalyses of two related image ciphers are introduced. Detailed theoretical derivations and extensive experiments confirmed the feasibility and efficiency of the proposed attacks. The related MATLAB codes are publicly available and can be found online.<\/jats:p>","DOI":"10.3233\/faia251660","type":"book-chapter","created":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T13:19:07Z","timestamp":1769519947000},"source":"Crossref","is-referenced-by-count":0,"title":["Cryptanalysis of Row-Column-Based Permutation Image Encryption Schemes with Known-Plaintext Attacks"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9143-6130","authenticated-orcid":false,"given":"Chengrui","family":"Zhang","sequence":"first","affiliation":[{"name":"Software College, Northeastern University, Shenyang, Liaoning, P. R. China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7863-1230","authenticated-orcid":false,"given":"Dongming","family":"Chen","sequence":"additional","affiliation":[{"name":"Software College, Northeastern University, Shenyang, Liaoning, P. R. China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2572-7658","authenticated-orcid":false,"given":"Dongqi","family":"Wang","sequence":"additional","affiliation":[{"name":"Software College, Northeastern University, Shenyang, Liaoning, P. R. China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3600-3062","authenticated-orcid":false,"given":"Mingzhao","family":"Xie","sequence":"additional","affiliation":[{"name":"Software College, Northeastern University, Shenyang, Liaoning, P. R. China"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining XI"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251660","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T13:19:08Z","timestamp":1769519948000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251660"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,27]]},"ISBN":["9781643686448"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251660","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,27]]}}}