A comprehensive study of Cybercrime and Digital Forensics through Machine Learning and AI

Abstract

Current need to fight evolving threats in the context of fast evolving threat landscape makes the field of digital forensics extremely challenging especially due to the rapidly growing cybercrime. This paper looks at how artificial intelligence (AI) and machine learning (ML) enhance the methods of artificial intelligence (AI) and machine learning (ML) to help digital forensic in cybercrime detection and evidence analysis, in furtherance, improving the overall years of a cyber-investigator. More and more sophisticated techniques like ransomware, phishing, and deepfake technology are being used by cybercriminals and no longer constantly working methods. From the law enforcement and cybersecurity professionals to forensic suits, AI driven tools offer an easy way to analyze large data sets efficiently, finding patterns and anomalies that would otherwise go unnoticed. Machine learning algorithms helps in automating the task of a classification of digital evidence and anomaly detection using supervised and unsupervised algorithms. Additionally, the study also assesses the effects of engineering innovations of RFM refinements, AI based automation and predictive analytics in cyber vigilance. The paper discusses the ethical considerations in this context, such as data privacy, algorithmic bias and transparency while talking about forensic AI applications. The paper also discusses how successful AI has been in law enforcement and private sector cybersecurity, two areas of life where AI is truly transforming. However, lack of regulatory standards, low levels of interdisciplinary teamwork, and insufficient training of relevant workforces are the main challenges that face the development of AI is potential while minimizing risk. Two future heads emphasize blockchain integration for evidence securely, quantum computing for rapid encryption, as well as cross-sectoral partnerships to pioneer in the footprint. Engineering principles and the application of AI driven automation can be leveraged to advance the discipline of digital forensics to a more proactive, adaptive state that furthers in the development of robust responses to cyber threats in a more and more interconnected world.