Knit scrambling: A novel image scrambling framework and its demonstration in image encryption

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dc.contributor.authorKaya, Muhammed Saadetdin
dc.contributor.authorInce, Kenan
dc.date.accessioned2026-04-04T13:34:59Z
dc.date.available2026-04-04T13:34:59Z
dc.date.issued2026
dc.departmentİnönü Üniversitesi
dc.description.abstractThe exponential growth of visual data and the expansion of resource-constrained IoT platforms have intensified the demand for lightweight yet secure image protection schemes. Conventional ciphers, while cryptographically strong, often fail to meet real-time and hardware-efficiency requirements for image data. To address this gap, this study presents the Knit Scrambling (KS) framework, a textile-inspired deterministic permutation framework designed for reversible image scrambling with linear computational cost. This approach models an image as a sequence interwoven from multiple subsequences following cyclic knitting patterns, ensuring both reversibility and high diffusion. A specific instantiation, termed Triple Check Pattern (TCP), realizes the KS framework by dividing the image into three subsequences and applying cyclic pattern rotations to enhance pixel decorrelation while preserving strict invertibility. The confusion process is integrated with a lightweight diffusion stage based on a key-nonce-derived chaotic keystream generated by a one-dimensional logistic map, eliminating plaintext dependence and enabling per-image uniqueness. Experimental analyses conducted on benchmark color images show near-uniform histograms, high entropy close to eight bits, and strong differential performance, with average NPCR around 99.6 percent and UACI approximately 33.5 percent. Statistical randomness evaluation using the NIST SP 800-22 test suite confirms the scheme's ability to produce unpredictable ciphertexts, while runtime benchmarking on both desktop and embedded-class hardware demonstrates real-time feasibility. The results indicate that the proposed framework provides an effective and hardware-efficient alternative to existing chaos-based and geometric scrambling approaches for lightweight image encryption in IoT environments. The proposed framework (KS) defines a general textile-inspired permutation model, while its implementation through the TCP algorithm demonstrates how this model can be practically realized to achieve efficient and reversible image scrambling.
dc.identifier.doi10.1016/j.jisa.2025.104326
dc.identifier.issn2214-2126
dc.identifier.issn2214-2134
dc.identifier.orcid0000-0003-1749-5604
dc.identifier.scopus2-s2.0-105024888426
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1016/j.jisa.2025.104326
dc.identifier.urihttps://hdl.handle.net/11616/109530
dc.identifier.volume97
dc.identifier.wosWOS:001642482300001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofJournal of Information Security and Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250329
dc.subjectPixel scrambling
dc.subjectImage encryption
dc.subjectLightweight encryption
dc.subjectLightweight cryptography
dc.titleKnit scrambling: A novel image scrambling framework and its demonstration in image encryption
dc.typeArticle

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