Deep Fake Detection in Images and Videos Using Spatial and Temporal Analysis

K. Subha, Aduri Sai Prateik, Gudla Sai Manikanta, Nistala Sri Harsha

2025

Abstract

The rapid progress of deep fake technology has created opportunities for innovation, but it also presents serious challenges to digital security and the integrity of media. Although deep fakes can be used for legitimate purposes in entertainment, their potential for abuse in spreading false information, committing identity theft, and influencing political narratives is a significant concern. Current detection methods struggle to keep up with the evolving sophistication of deep fake techniques. This paper presents a deep fake detection system that accurately identifies manipulated images and videos. The system utilizes deep learning frameworks, including Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, to detect irregularities in facial expressions, lighting conditions, and motion dynamics, providing a more effective solution to combat the risks posed by deep fakes.

Paper Citation

in Harvard Style

Subha K., Prateik A., Manikanta G. and Harsha N. (2025). Deep Fake Detection in Images and Videos Using Spatial and Temporal Analysis. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 478-482. DOI: 10.5220/0013885100004919

in Bibtex Style

@conference{icrdicct`2525,
author={K. Subha and Aduri Prateik and Gudla Manikanta and Nistala Harsha},
title={Deep Fake Detection in Images and Videos Using Spatial and Temporal Analysis},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={478-482},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013885100004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Deep Fake Detection in Images and Videos Using Spatial and Temporal Analysis
SN - 978-989-758-777-1
AU - Subha K.
AU - Prateik A.
AU - Manikanta G.
AU - Harsha N.
PY - 2025
SP - 478
EP - 482
DO - 10.5220/0013885100004919
PB - SciTePress