Advancing Video Encryption with Real-Time Parallel Computing Strategy: Conclusion
by MultiThreading.Tech: #1 Publication on Concurrent ProgrammingMarch 16th, 2024
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The conclusion highlights the innovative real-time video encryption strategy using parallel computing techniques, showcasing enhanced encryption speed, statistical properties, and security resilience. This breakthrough provides a new path for video encryption research and applications, ensuring advanced security measures.
Authors:
(1) Dong Jiang, School of Internet, Anhui University, National Engineering Research Center of Agro-Ecological Big Data Analysis and Application, Anhui University & [email protected];
(2) Zhen Yuan, School of Internet, Anhui University;
(3) Wen-xin Li, School of Internet, Anhui University;
(4) Liang-liang Lu, Key Laboratory of Optoelectronic Technology of Jiangsu Province, Nanjing Normal University, National Laboratory of Solid State Microstructures, Nanjing University, Nanjing & [email protected].
Table of Links
8. Conclusion
To sum up, a parallel computing technique based real-time chaotic video encryption strategy is proposed in this paper. It uses multiple threads to simultaneously perform confusion and diffusion operations on corresponding subframes to improve the computational efficiency. To evaluate the performance of the strategy, two chaotic maps are selected to implement cryptosystems. The encryption speed evaluation prove that such strategy significantly improves the encryption speed, and realizes realtime video encryption with different hardware platforms. The statistical and security analysis show that the deployed cryptosystems have outstanding statistical properties and resistance to attacks, noise, and data loss. Compared with previous works, the proposed strategy, to the best of our knowledge, achieves the fastest encryption speed, realizes the first real-time video encryption based on multiple-round confusion-diffusion architecture. This paper provides a feasible solution and a new path for related applications and research, respectively.
CRediT authorship contribution statement
Dong Jiang: Conceptualization, Methodology, Writingoriginal draft, Software, Supervision. Zhen Yuan: Investigation, Methodology, Software . Wen-xin Li: Investigation, Software. Liang-liang Lu: Conceptualization, Methodology, Writing - review & editing, Supervision.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data availability
Data will be made available on request.
This paper is available on arxiv under CC 4.0 license.
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