A Recent Systematic Review of Ransomware Attack detection in machine learning techniques
Ransomware attacks have emerged as a significant threat to organizations and individuals, causing substantial financial and operational damages worldwide. With the increasing sophistication and frequency of ransomware attacks, it is crucial to develop effective detection mechanisms to identify and m...
| Published in: | 2023 4th International Conference on Artificial Intelligence and Data Sciences: Discovering Technological Advancement in Artificial Intelligence and Data Science, AiDAS 2023 - Proceedings |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
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Institute of Electrical and Electronics Engineers Inc.
2023
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176616525&doi=10.1109%2fAiDAS60501.2023.10284709&partnerID=40&md5=16b0734025f603d3b0ed8348472e9670 |
| Summary: | Ransomware attacks have emerged as a significant threat to organizations and individuals, causing substantial financial and operational damages worldwide. With the increasing sophistication and frequency of ransomware attacks, it is crucial to develop effective detection mechanisms to identify and mitigate these threats. Machine learning techniques have gained prominence in detecting ransomware attacks due to their ability to analyze large volumes of data and identify patterns indicative of malicious activities. This systematic review aims to provide a comprehensive analysis of the existing literature on ransomware attack detection using machine learning techniques. © 2023 IEEE. |
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| DOI: | 10.1109/AiDAS60501.2023.10284709 |