A Recent Systematic Review of Ransomware Attack detection in machine learning techniques

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...

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Published in:2023 4th International Conference on Artificial Intelligence and Data Sciences: Discovering Technological Advancement in Artificial Intelligence and Data Science, AiDAS 2023 - Proceedings
Main Author: Ahmad S.; Zulkifli Z.; Nasarudin N.H.; Imran M.; Ariff M.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2023
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176616525&doi=10.1109%2fAiDAS60501.2023.10284709&partnerID=40&md5=16b0734025f603d3b0ed8348472e9670
id 2-s2.0-85176616525
spelling 2-s2.0-85176616525
Ahmad S.; Zulkifli Z.; Nasarudin N.H.; Imran M.; Ariff M.
A Recent Systematic Review of Ransomware Attack detection in machine learning techniques
2023
2023 4th International Conference on Artificial Intelligence and Data Sciences: Discovering Technological Advancement in Artificial Intelligence and Data Science, AiDAS 2023 - Proceedings


10.1109/AiDAS60501.2023.10284709
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176616525&doi=10.1109%2fAiDAS60501.2023.10284709&partnerID=40&md5=16b0734025f603d3b0ed8348472e9670
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.
Institute of Electrical and Electronics Engineers Inc.

English
Conference paper
author Ahmad S.; Zulkifli Z.; Nasarudin N.H.; Imran M.; Ariff M.
spellingShingle Ahmad S.; Zulkifli Z.; Nasarudin N.H.; Imran M.; Ariff M.
A Recent Systematic Review of Ransomware Attack detection in machine learning techniques
author_facet Ahmad S.; Zulkifli Z.; Nasarudin N.H.; Imran M.; Ariff M.
author_sort Ahmad S.; Zulkifli Z.; Nasarudin N.H.; Imran M.; Ariff M.
title A Recent Systematic Review of Ransomware Attack detection in machine learning techniques
title_short A Recent Systematic Review of Ransomware Attack detection in machine learning techniques
title_full A Recent Systematic Review of Ransomware Attack detection in machine learning techniques
title_fullStr A Recent Systematic Review of Ransomware Attack detection in machine learning techniques
title_full_unstemmed A Recent Systematic Review of Ransomware Attack detection in machine learning techniques
title_sort A Recent Systematic Review of Ransomware Attack detection in machine learning techniques
publishDate 2023
container_title 2023 4th International Conference on Artificial Intelligence and Data Sciences: Discovering Technological Advancement in Artificial Intelligence and Data Science, AiDAS 2023 - Proceedings
container_volume
container_issue
doi_str_mv 10.1109/AiDAS60501.2023.10284709
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176616525&doi=10.1109%2fAiDAS60501.2023.10284709&partnerID=40&md5=16b0734025f603d3b0ed8348472e9670
description 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.
publisher Institute of Electrical and Electronics Engineers Inc.
issn
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
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