Video security against deepfakes and other forgeries. (17th February 2020)

• Record Type: Journal Article
• Authors: Sethi, Lastika; Dave, Anay; Bhagwani, Raj; Biwalkar, Ameyaa
• Is Part Of: Journal of discrete mathematical sciences & cryptography. Volume 23:Number 2(2020)
• Page Start: 349
• Page End: 363
• Publication Date: 2020-02-17
• Subjects: 65D99; AES encryption -- Authentication -- DeepFakes -- Haar Cascades -- Local Binary Pattern Histogram method -- Ownership -- Semi-fragile watermarking; Computer science -- Mathematics -- Periodicals; Cryptography -- Periodicals; Computer science -- Mathematics; Cryptography; Periodicals; 004.0151
• DOI: 10.1080/09720529.2020.1721866
• Languages: English
• ISSNs: 0972-0529

Abstract

Abstract: This paper describes a system of steps which aims at proving the ownership of video content, detecting tampered original videos and distinguishing between authentic and counterfeit videos. This system achieves its purpose by using the interdisciplinary technologies of image processing namely face detection, recognition and semi fragile watermarking along with data security algorithm of AES encryption. Our paper aims at optimizing each step in this system to reduce the overall computational count.