A comprehensive survey on digital video forensics: Taxonomy, challenges, and future directions. (November 2021)

• Record Type: Journal Article
• Authors: Javed, Abdul Rehman; Jalil, Zunera; Zehra, Wisha; Gadekallu, Thippa Reddy; Suh, Doug Young; Piran, Md. Jalil
• Is Part Of: Engineering applications of artificial intelligence. Volume 106(2021)
• Publication Date: 2021-11
• Subjects: Digital forensics -- Anti-forensics -- Machine learning (ML) -- Deep learning (DL) -- Computer vision (CV) -- Video forensics -- Video forgery -- Evidence extraction -- Forgery detection -- Legal aspects; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2021.104456
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: With the explosive advancements in smartphone technology, video uploading/downloading has become a routine part of digital social networking. Video contents contain valuable information as more incidents are being recorded now than ever before. In this paper, we present a comprehensive survey on information extraction from video contents and forgery detection. In this context, we review various modern techniques such as computer vision and different machine learning (ML) algorithms including deep learning (DL) proposed for video forgery detection. Furthermore, we discuss the persistent general, resource, legal, and technical challenges, as well as challenges in using DL for the problem at hand, such as the theory behind DL, CV, limited datasets, real-time processing, and the challenges with the emergence of ML techniques used with the Internet of Things (IoT)-based heterogeneous devices. Moreover, this survey presents prominent video analysis products used for video forensics investigation and analysis. In summary, this survey provides a detailed and broader investigation about information extraction and forgery detection in video contents under one umbrella, which was not presented yet to the best of our knowledge.