网络与信息安全学报 ›› 2017, Vol. 3 ›› Issue (2): 46-52.doi: 10.11959/j.issn.2096-109x.2017.00123

• 学术论文 • 上一篇    下一篇

视频目标移除篡改的被动取证

姚晔(),胡伟通,任一支   

  1. 杭州电子科技大学网络空间安全学院,浙江 杭州 310018
  • 修回日期:2016-11-15 出版日期:2017-02-01 发布日期:2017-02-10
  • 作者简介:姚晔(1978-),男,湖北随州人,博士,杭州电子科技大学讲师,主要研究方向为多媒体安全、视频智能分析。|胡伟通(1986-),男,浙江乐清人,博士,杭州电子科技大学讲师,主要研究方向为多媒体安全、移动终端安全。|任一支(1981-),男,安徽安庆人,博士,杭州电子科技大学副教授,主要研究方向为社会计算、网络安全。
  • 基金资助:
    上海市信息安全综合管理技术研究重点实验室开放基金资助项目(AGK2015004);家重点实验室开放基金资助项目(14S01)

Passive forensics for video object removal tampering

Ye YAO(),Wei-tong HU,Yi-zhi REN   

  1. School of CyberSpace Security, Hangzhou Dianzi University, Hangzhou 310018, China
  • Revised:2016-11-15 Online:2017-02-01 Published:2017-02-10
  • Supported by:
    The Open Research Fund of Shanghai Key Laboratory of Integrated Administration Technologies for Infor-mation Security(AGK2015004);The Open Research Fund of State Key Laboratory of Information Engineering in Survey-ing, Mapping and Remote Sensing(14S01)

摘要:

首先,对数字视频目标移除篡改的被动取证概念及重要性进行了介绍;然后,选择了几种具有代表性的视频目标移除篡改被动取证算法,并将这些算法按照未来发展趋势分为基于相关性分析的被动取证和基于机器学习的被动取证这两大类,详细介绍了这几种算法的主要步骤和过程;最后,对本领域未来的研究趋势进行了展望。

关键词: 数字视频取证, 视频目标移除篡改, 篡改检测, 被动取证

Abstract:

Firstly, the concept and importance of digital video object removal tampering forensics were introduced. Then, several current passive forensics algorithms for object removal tampering were selected and divided into two categories that based on correlation analysis and based on machine learning algorithm according to development trends. The selected passive forensics algorithms were introduced in detail. Finally, some possible research trends in video object removal tampering detections in the future were looked forward to.

Key words: digital video forensics, video object tampering, tampering detection, passive forensics

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