mlsanityData to 14 Oct 2026

Machine Learning and Deep Learning Techniques used in Cybersecurity and Digital Forensics: a Review

arXiv 2501.03250 ↗First posted 24 Dec 2024cs.CR cs.AIcited by 0

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Abstract (arXiv)

In the paced realms of cybersecurity and digital forensics machine learning (ML) and deep learning (DL) have emerged as game changing technologies that introduce methods to identify stop and analyze cyber risks. This review presents an overview of the ML and DL approaches used in these fields showcasing their advantages drawbacks and possibilities. It covers a range of AI techniques used in spotting intrusions in systems and classifying malware to prevent cybersecurity attacks, detect anomalies and enhance resilience. This study concludes by highlighting areas where further research is needed and suggesting ways to create transparent and scalable ML and DL solutions that are suited to the evolving landscape of cybersecurity and digital forensics.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). First posted on arXiv 24 Dec 2024.

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