Artificial Intelligence-Driven Forensic Analysis of Digital Images for Cybersecurity Investigations
Keywords:
Artificial Intelligence, Forensic Analysis, Digital Images, Cybersecurity Investigations, Image Tampering, Deep Learning, Feature Extraction, Image Forgery Detection, Interpretability, Adversarial ResilienceAbstract
The current world is highly circumscribed by these numerous threats hence providing a basis for developing better ways of handling images for cybersecurity purposes specifically in the field of cyber forensics. This paper aims to compare and analyse how AI can be implemented to increase the effectiveness and timeframe of forensic analysis of digital images. By employing machine learning methods, we describe the current and emerging trends in image forensics, identifying the key issues regarding image tampering detection and attribution. In this paper, we establish a justification of the use of AI methods in the manipulation of forged images, with the aim of using such findings to help in cybercrime investigations. In addition, identifying the pros and cons of the integration of AI technologies within forensic analysis, we also highlight the ethical concerns and legal consequences that arise with the use of AI technologies in analysis. Overall, this work aims to progress the knowledge regarding AI utilization in the context of cybersecurity and offer suggestions for future study of this essential field.
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