{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/cryptanalyzing-an-image-encryption-algorithm-1","title":"Cryptanalyzing an Image Encryption Algorithm Underpinned by 2D Lag-Complex Logistic Map","arxiv_id":"2208.06774","date":"2022-08-14","proceeding":null,"authors":["Chengqing Li","Xianhui Shen","Sheng Liu"],"abstract":"This paper analyzes security performance of an image encryption algorithm using 2D lag-complex Logistic map (LCLM), which adopts it as a pseudo-random number generator, and uses the sum of all pixel values of the plain-image as its initial value to control the random combination of the basic encryption operations. However, multiple factors make the final pseudo-random sequences controlling the encryption process may be the same for different plain-images. Based on this point, we proposed a chosen-plaintext attack by attacking the six encryption steps with a strategy of divide and conquer. Using the pitfalls of 2D-LCLM, the number of required chosen plain-images is further reduced to $5\\cdot\\log_2(MN)+95$, where $\\mathit{MN}$ is the number of pixels of the plain-image.","url_abs":"https://arxiv.org/abs/2208.06774v1","url_pdf":"https://arxiv.org/pdf/2208.06774v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"cryptanalyzing-an-image-encryption-algorithm-1","repo_url":"https://github.com/chengqingli/mm-iealm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}