arrow
返回

ESKVS: efficient and secure approach for keyframes-based video summarization framework

delete2024-02-17
delete4
PRE
AI
P
Parul Saini *
K
Krishan Berwal
DOI:10.1007/s11042-024-18405-7delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Video security has emerged as a critical study issue in multimedia security in recent years as videos are the most effective and widely used multimedia format. They immediately establish a connection with users. It is necessary to prevent this sensitive information from being stolen or destroyed in various domains, including the military, finance, and education. It can be achieved by either hiding its significance, turning it into a secret code through encryption, or doing both simultaneously. Because video data is generated, transmitting it securely is challenging, and there is resource wastage of memory, processing, and bandwidth. Users must spend a lot of time and effort scanning through this enormous amount of video information in search of the required information. Therefore, a secure keyframes-based generic video summarization (VS) model is proposed to generate a secure video summary. First, Secret Keyframes (SKs) are extracted from the video through proposed Probability VS (PBVS) and Extended (E-PBVS). Second, multi-secret image sharing is provided to the SKs by the proposed EBEMSS (Enhanced Blockwise Encryption based Multi Secret Sharing) scheme, which uses a polynomial congruence concept for keyframe security. The proposed model E-PBVS achieved an average F-score of 0.76 and 0.81 on two benchmark (OV and YT) datasets, respectively, showing its effectiveness in producing informative video summaries. Additionally, EBEMSS outperforms the other related security models. The proposed model outperforms with generated summary and security compared to other keyframe-based VS and MSS techniques.
Keyword:
Video security
Multi-secret sharing
Clustering
Encryption
Multimedia security
Secure image

期刊

Multimedia Tools and Applications 封面图
Multimedia Tools and Applications
IF:
3
论文数:
1.9W
被引数:
3.2W

机构

暂无机构信息
引用论文

引用论文

err分享
err收藏
Optimal Series Resistors for On-Wafer Calibrations晶圆上校准的最佳串联电阻
err2020-01-01
err0
PREAI
errJasper A. Drisko; Richard A. Chamberlin; James C. Booth; Nathan D. Orloff; Christian J. Long
err分享
err收藏
err分享
err收藏
Formation of palladium hydride nanoparticles in Pd/C catalyst as evidenced by in situ XAS data
err2010-03-23
err0
PREAI
errA. Yu. Stakheev; I. C. Mashkovskii; O. P. Tkachenko; K. V. Klementiev; W. Grünert; G. N. Baeva; L. M. Kustov
err分享
err收藏
Video summarization using deep learning techniques: a detailed analysis and investigation
err2023-03-15
err16
errOAAI
errSaini, Parul; Kumar, Krishan; Kashid, Shamal; Saini, Ashray; Negi, Alok
err分享
err收藏
Kostenvergleichskalkulation der Schlitten- vs. bikondylären Oberflächenversorgung am Kniegelenk
err2011-12-09
err0
PREAI
errR. Kasch; S. Merk; R. Kayser; A. Lahm; W. Drescher; A. Schulz; T. Wilke; S. Flessa
err分享
err收藏
Predictive systems models can help elucidate bee declines driven by multiple combined stressors
err2016-10-24
err0
errOAAI
errMickaël Henry; Matthias A. Becher; Juliet L. Osborne; Peter J. Kennedy; Pierrick Aupinel; Vincent Bretagnolle; François Brun; Volker Grimm; Juliane Horn; Fabrice Requier
err分享
err收藏
学者 查看更多内容