Every Month Last Day ISSN (online): 1934-9955

International Journal Of Imaging

Science And Engineering

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Abstract

DEEPFAKE DETECTION A SYSTEMATIC LITERATURE REVIEW

Author: Dasari Shirisha, M Harshitha Goud, Vaddeman Swetha, Ganta Vijay Kumar

Abstract:

Artificial intelligence (AI), machine learning (ML), and deep learning (DL) have all made tremendous strides in the recent few decades, opening up new possibilities for the manipulation of multimedia. Even while most people have utilised the technology for good, such in entertainment and education, some bad apples have found a way to get their hands on it and do evil. As an example, individuals have made convincingly phoney movies, photos, or audios to annoy and blackmail others, propagate false information and propaganda, or incite political strife and hatred. Recently, the term "Deepfake" has been used to describe these doctored, high-quality, and convincing films. In response to Deepfake's concerns, other methods have been detailed in the literature. In this study, we do a systematic literature review (SLR) to provide a current synopsis of Deepfake detection research. The publications range in date from 2018 to 2020 and cover a variety of approaches. Methods based on deep

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