基于人工免疫的数字视频篡改取证方法研究  

Research on Digital Video Tampering Forensics Method Based on Artificial Immune

作　　者：徐子栋 张中 XU Zidong;ZHANG Zhong(Institute of Evidence Law and Forensic Science,China University of Political Science and Law,Beijing 100088,China)

机构地区：[1]中国政法大学证据科学研究院,北京100088

出　　处：《吉林大学学报（信息科学版）》2022年第1期30-35,共6页Journal of Jilin University（Information Science Edition）

基　　金：国家自然科学基金面上基金资助项目(71874013)。

摘　　要：针对目前采用的方法对数字视频进行篡改取证时,没有对数字视频进行去噪处理,导致取证误差大、视频缺失值高以及视频变形严重的问题。提出了基于人工免疫的数字视频篡改取证方法。该方法通过中值滤波器初步对数字视频进行滤波处理,并对数字视频进行相似块匹配,根据匹配结果建立三阶张量,根据张量和噪声的性质结合增广拉格朗日乘子法消除数字视频中存在的噪声。采用人工免疫算法构建自体动态演化模型和抗原动态演化模型,在此基础上建立数字视频篡改取证模型,将去噪后的数字视频输入模型中,实现数字视频的篡改取证。实验结果表明,所提方法的取证误差小,视频缺失值低,视频变形系数小。The current method for digital video tampering, no denoising, results in forensic error, high missing value and serious video distortion. Based on artificial immunity digital video tampering method, preliminary filter through the median filter, and similar blocks, a third order tensor is established according to the matching results, according to the nature of the tensor and noise to eliminate the Lagrange multiplier noise.Artificial immunity algorithm is used to build the autodynamic evolution model and the antigen dynamic evolution model, based on the digital video tampering forensics model to realize the forensics of digital video tampering in the denoised digital video input model. The experimental results show that the proposed method has small forensic error, low video missing value and small video deformation coefficient.

关 键 词：人工免疫算法 数字视频 视频去噪 视频篡改取证 中值滤波器 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]