Temporal action segmentation for video encryption

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dc.contributor.authorGao, Suo
dc.contributor.authorIu, Herbert Ho-Ching
dc.contributor.authorMou, Jun
dc.contributor.authorErkan, Uğur
dc.contributor.authorLiu, Jiafeng
dc.contributor.authorWu, Rui
dc.contributor.authorTang, Xianglong
dc.date.accessioned2025-01-12T17:19:41Z
dc.date.available2025-01-12T17:19:41Z
dc.date.issued2024
dc.departmentKMÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractVideos contain temporal information, enabling them to capture the dynamic changes of actions and provide richer visual effects. Traditional video encryption methods involve decomposing videos into frames and encrypting them frame by frame, which results in significant resource consumption. This paper proposes a video encryption method based on temporal action segmentation. This methodology involves the identification and extraction of pivotal frames from a video dataset, followed by the encryption of these significant key frames. This approach serves to enhance the efficacy of the video encryption algorithm. The method consists of three modules. The first module uses temporal action segmentation to classify video frames and extract important frames for the second module's input. The second module encrypts the extracted key frames using a chaos-based encryption algorithm, thereby reducing the time cost of video encryption. The third module outputs the encrypted video. During the encryption process, a large amount of key stream is required. To address this, the paper introduces a new pseudo-random sequence generation method called two-dimensional Gramacy&Lee map (2D-GLM). Comprehensive comparative analysis clearly demonstrates that compared to other systems, 2D-GLM exhibits superior performance and can generate a large number of high-performance pseudo-random sequences. The proposed algorithm is tested on GTEA, and the simulation results demonstrate that it can accomplish video encryption tasks with high security.
dc.description.sponsorshipNational Natural Science Founda-tion of China [61672190]; China Scholarship Council (CSC) [CSC202306120290]
dc.description.sponsorshipAcknowledgments This research is supported by the National Natural Science Founda-tion of China (No. 61672190) ; China Scholarship Council (CSC) , No. CSC202306120290.
dc.identifier.citationGao, S., Iu, H. H.-C., Mou, J., Erkan, U., Liu, J., Wu, R., & Tang, X. (2024). Temporal action segmentation for video encryption. Chaos, Solitons and Fractals: The Interdisciplinary Journal of Nonlinear Science, and Nonequilibrium and Complex Phenomena, 183. https://doi.org/10.1016/j.chaos.2024.114958
dc.identifier.doi10.1016/j.chaos.2024.114958
dc.identifier.issn0960-0779
dc.identifier.issn1873-2887
dc.identifier.scopus2-s2.0-85192228470
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.chaos.2024.114958
dc.identifier.urihttps://hdl.handle.net/11492/10157
dc.identifier.volume183
dc.identifier.wosWOS:001239973900001
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Sceince
dc.indekslendigikaynakScopus
dc.institutionauthorErkan, Uğur
dc.institutionauthoridErkan, Uğur/0000-0002-2481-0230
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltd
dc.relation.ispartofChaos Solitons & Fractals
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectCryptography
dc.subjectVideo Encryption
dc.subjectChaos
dc.subjectTemporal Action Segmentation
dc.titleTemporal action segmentation for video encryption
dc.typeArticle

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