内蒙古民族大学学报（自然科学版）2024，Vol.39Issue(4)：52-55,4.DOI:10.14045/j.cnki.15-1220.2024.04.010
基于深度学习的视频篡改检测方法
Video Tampering Detection Method Based on Deep Learning
摘要
Abstract
With the rapid development of the new generation of information technology,the application of multi-media technology for video or image processing is becoming more and more widespread,and the authenticity of digi-tal videos faces huge challenges.In this paper,a video tampering detection algorithm based on deep learning is pro-posed:the Convolutional Neural Network(CNN)is combined with the Long Short-Term Memory(LSTM)network,and the Hash algorithm is integrated,the features extracted by the convolutional neural network are input into the long-term and short-term memory network model,and the spatial and temporal features are extracted through the fully connected layer Softmax to construct CNNH-LSTM in the fusion model.By applying this network model to live video tampering detection and classification,the experimental results show that the model has good feature extraction capability generalization capability,and good distinguishing,providing a new method for video tamper detection.关键词
神经网络/哈希算法/视频篡改Key words
neural networks/Hash algorithm/video tampering分类
信息技术与安全科学引用本文复制引用
陈雪艳,梁大超,宋启东,王洪泰..基于深度学习的视频篡改检测方法[J].内蒙古民族大学学报（自然科学版）,2024,39(4):52-55,4.基金项目
国家自然科学基金项目(61440041) （61440041）
内蒙古自治区青年科技英才项目(NJYT22051) （NJYT22051）
内蒙古自治区高等学校科学技术重点项目(NJZZ19144) （NJZZ19144）
内蒙古自治区直属高校基本科研业务费项目(GXKY22045) （GXKY22045）
