A chaotic-based watermarking scheme for ensuring integrity of a face recognition system in public large gathering scenario

Basil Saud Alhazmi,Oussama Benrhouma,Adnan Nadeem Alhassan,Muhammad Ashraf, Saad Said Alqahtany

JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES(2023)

引用 0|浏览4
暂无评分
摘要
Secure data transmission is critical in public video surveillance applications such as tracking missing persons in large crowd gatherings. It may help the security personnel to monitor & record the live feeds from multiple cameras. However, this live streaming could be falsified. Various cryptographic techniques have been proposed to ensure the integrity of transmitted images, but continuous attacks still pose serious challenges to ensuring the integrity and authenticity of transmitted images. This work proposes a new chaotic-based watermarking technique to ensure the integrity of the transmitted video frames, and since the frames come from multiple cameras, the scheme should be as simple as possible and as fast as possible, the simplicity manifests in designing a fragile watermarking scheme therefore, the watermark is to be embedded in the spatial domain by direct manipulation of the values of the cover's pixels. To ensure the security of the proposed scheme, chaotic maps have been deployed to reach an acceptable level of security with minimum computational overhead. The proposed scheme is novel in design in terms of the chaotic maps used and it is tested in challenging large gathering scenario. Experimental results demonstrate that the proposed method successfully locates any falsification in the transmitted images, and the performance of the scheme evaluates different types of attacks. Our testing results in good rate tamper of detection with TPR = 99.2005, TNR = 99.0777 and with a good quality of imperceptibility for the watermarked image with PSNR = 43.82 dB, SSIM = 00.9955.
更多
查看译文
关键词
Watermark,Least Significant Bits (LSBs),Face detection,Chaotic systems,Tamper detection
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要