DeepFakes: Detecting Forged and Synthetic Media Content Using Machine Learning

Sm Zobaed, Fazle Rabby, Istiaq Hossain, Ekram Hossain, Sazib Hasan, Asif Karim, Khan Md. Hasib

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

13 Citations (Scopus)


The rapid advancement in deep learning makes the differentiation of authentic and manipulated facial images and video clips unprecedentedly harder. The underlying technology of manipulating facial appearances through deep generative approaches, enunciated as DeepFake that have emerged recently by promoting a vast number of malicious face manipulation applications. Subsequently, the need of other sort of techniques that can assess the integrity of digital visual content is indisputable to reduce the impact of the creations of DeepFake. A large body of research that are performed on DeepFake creation and detection create a scope of pushing each other beyond the current status. This study presents challenges, research trends, and directions related to DeepFake creation and detection techniques by reviewing the notable research in the DeepFake domain to facilitate the development of more robust approaches that could deal with the more advance DeepFake in future.

Original languageEnglish
Title of host publicationArtificial Intelligence in Cyber Security: Impact and Implications
Subtitle of host publicationSecurity Challenges, Technical and Ethical Issues, Forensic Investigative Challenges
EditorsReza Montasari, Hamid Jahankhani
Place of PublicationCham, Switzerland
PublisherSpringer Nature
Number of pages25
ISBN (Electronic)978-3-030-88040-8
ISBN (Print)978-3-030-88039-2, 978-3-030-88042-2
Publication statusPublished - 2021

Publication series

NameAdvanced Sciences and Technologies for Security Applications
ISSN (Print)1613-5113
ISSN (Electronic)2363-9466

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Copyright 2021 Elsevier B.V., All rights reserved.


Dive into the research topics of 'DeepFakes: Detecting Forged and Synthetic Media Content Using Machine Learning'. Together they form a unique fingerprint.

Cite this