Machine Learning and Deep Learning Techniques used in Cybersecurity and Digital Forensics: a Review
December 24, 2024 ยท The Cartographer ยท ๐ arXiv.org
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"Title-pattern auto-detect: Machine Learning and Deep Learning Techniques used in Cybersecurity and Digital Forensics: a Review"
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Authors
Jaouhar Fattahi
arXiv ID
2501.03250
Category
cs.CR: Cryptography & Security
Cross-listed
cs.AI
Citations
11
Venue
arXiv.org
Last Checked
3 days ago
Abstract
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.
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