Detecting Deepfakes: Exploring the Frontiers of Deepfake Generation and Detection

The advent of deepfake technology has increased various cybersecurity vulnerabilities.Mitigating these threats poses a significant challenge due to the realistic nature and difficulty of detecting deepfakes.The rise of AI-driven tools introduces additional intricacy and intrigue to generating exceptionally realistic deepfake images.The photos generated by these technologies exhibit a remarkable level of realism, making it extremely difficult for human observers to differentiate between deepfake and real images.To better understand recent advances, we explored state-of-the-art techniques in image generation.Our investigation reveals a gap in the existing literature: There are no datasets of fake faces in the Indian context.To address this, we develop a web application capable of generating high-quality fake faces and creating a dataset of Indian fake faces.In addition, we develop an Android application specifically for deepfake detection tasks.

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Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1145/3734947.3734956
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
0.00

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article

Detecting Deepfakes: Exploring the Frontiers of Deepfake Generation and Detection

Surbhi Raj, Jimson Mathew, Arijit Mondal
Generative Adversarial Networks and Image Synthesis
article

Detecting Deepfakes: Exploring the Frontiers of Deepfake Generation and Detection

Surbhi Raj, Jimson Mathew, Arijit Mondal
article en

Abstract

The advent of deepfake technology has increased various cybersecurity vulnerabilities.Mitigating these threats poses a significant challenge due to the realistic nature and difficulty of detecting deepfakes.The rise of AI-driven tools introduces additional intricacy and intrigue to generating exceptionally realistic deepfake images.The photos generated by these technologies exhibit a remarkable level of realism, making it extremely difficult for human observers to differentiate between deepfake and real images.To better understand recent advances, we explored state-of-the-art techniques in image generation.Our investigation reveals a gap in the existing literature: There are no datasets of fake faces in the Indian context.To address this, we develop a web application capable of generating high-quality fake faces and creating a dataset of Indian fake faces.In addition, we develop an Android application specifically for deepfake detection tasks.

Indian Institute of Technology Patna (IN)
Indian Institute of Technology Kharagpur
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Openalex Percentile: Top 69%
Generative Adversarial Networks and Image Synthesis
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Detecting Deepfakes: Exploring the Frontiers of Deepfake Generation and Detection — Surbhi Raj, Jimson Mathew, et al. · (2024) | TGRS Research Map | TGRS