Book Title: Modern Forensic Tools and Devices: Trends in Criminal Investigation
Editors: Mr. Ravi Kumar, Ms. Nandini Katare, Don Caeiro, and Dr. Surbhi Girdhar
Chapter: 10
DOI: https://doi.org/10.59646/658/10
Author: Aswathi Chandran Nair
Abstract
In the contemporary digital landscape, the pervasive nature of multimedia content encompassing audio, video, and images has revolutionized communication, entertainment, and information dissemination across diverse platforms, particularly social media. However, this ubiquity has also given rise to significant challenges regarding the authenticity and integrity of digital media, necessitating robust forensic techniques to discern legitimate content from various forms of manipulation and forgery (Al-Fehani & Al-Kuwari, 2024). The sophistication of modern editing tools and advanced AI-based generation techniques, such as deepfakes, exacerbates this challenge, making the detection of forgeries a critical and complex endeavor (Bhagtani et al., 2022; Indore, 2025). This chapter delves into the intricate methodologies employed in audio, video, and image forensics, exploring both passive and active authentication techniques designed to identify alterations, verify origins, and assess the overall integrity of digital media. It also examines the evolving landscape of multimedia manipulation, emphasizing the critical role of deep learning in addressing emerging threats to content authenticity (Diwan, 2023). This includes an in-depth analysis of methodologies for detecting subtle modifications, such as double compression or blurring, alongside more overt manipulations like splicing, copy-move forgery, and the addition or deletion of video frames (Amerini et al., 2021). The field of multimedia forensics thus stands as a crucial discipline dedicated to the scientific analysis of these digital signals, aiming to recover evidentiary traces and establish the provenance and integrity of the data (Ekhande et al., 2022). The immense increase in multimedia content across the internet, driven by various applications, has unfortunately led to a corresponding rise in threats from manipulated or maliciously used content. This necessitates advanced forensic methodologies to authenticate digital media and ascertain its integrity against increasingly sophisticated manipulation techniques (Verdoliva, 2020). This interdisciplinary field draws upon signal processing, computer vision, machine learning, and statistical analysis to address fundamental questions of authenticity and source identification.