Analysis of electronic bill authentication and security storage performance utilising machine learning algorithm
Jingcheng Tian, Lingbo Yang, Yutao Zhang, Wei Qian · International Journal of Grid and Utility Computing · 2022
The study aims to ensure the security and authentication efficiency of the bill image, and the encryption and decryption methods and security protection of the electronic bill are studied in the experiment. First, aiming at the not high traditional electronic bill security performance, a method is proposed, namely, embedding a watermark into a binary image with edge information. Second, aiming at the weak compression robust character of electronic bill image, the method of chaotic encryption of digital watermark through wavelet coefficient matrix algorithm is proposed to be combined with the binary sequence. Finally, the deep learning algorithm combined with the convolution algorithm can detect the quality of electronic bill watermark images. The results show that the method of embedding watermark with edge information effectively has improved the confidentiality of electronic bills. The method of chaotic encryption of digital watermarks by wavelet coefficient matrix algorithm combined with binary sequence has improved the anti-compression ability of digital watermarks. The multi-watermark encryption method has enhanced the tamper-proof ability of electronic bills and has improved the security performance of bills, and the deep convolution algorithm has improved the security and efficiency of electronic bill processing.