A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity

<p dir="ltr">The use of artificial intelligence (AI) technology signifies a significant milestone in the swiftly evolving domain of cybersecurity. This study offers a comprehensive literature review on the role, effect, and future prospects of AI across five critical areas of cyberse...

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Main Author: Abdullah Al Siam (22304047) (author)
Other Authors: Moutaz Alazab (17730060) (author), Albara Awajan (20083410) (author), Nuruzzaman Faruqui (19748945) (author)
Published: 2025
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author Abdullah Al Siam (22304047)
author2 Moutaz Alazab (17730060)
Albara Awajan (20083410)
Nuruzzaman Faruqui (19748945)
author2_role author
author
author
author_facet Abdullah Al Siam (22304047)
Moutaz Alazab (17730060)
Albara Awajan (20083410)
Nuruzzaman Faruqui (19748945)
author_role author
dc.creator.none.fl_str_mv Abdullah Al Siam (22304047)
Moutaz Alazab (17730060)
Albara Awajan (20083410)
Nuruzzaman Faruqui (19748945)
dc.date.none.fl_str_mv 2025-01-23T09:00:00Z
dc.identifier.none.fl_str_mv 10.1109/access.2025.3528114
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/A_Comprehensive_Review_of_AI_s_Current_Impact_and_Future_Prospects_in_Cybersecurity/30198469
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Machine learning
Artificial intelligence
cyber security
cyberattack
machine learning
deep learning
Computer security
Security
Threat assessment
Natural language processing
Real-time systems
Malware
Machine learning
Electronic mail
Adaptation models
dc.title.none.fl_str_mv A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">The use of artificial intelligence (AI) technology signifies a significant milestone in the swiftly evolving domain of cybersecurity. This study offers a comprehensive literature review on the role, effect, and future prospects of AI across five critical areas of cybersecurity: threat detection, endpoint security, phishing and fraud detection, network security, and adaptive authentication. The study examines contemporary developments in AI for cybersecurity, highlighting the use of these technologies to enhance security protocols. We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. Essential comparisons of AI models are presented for each area, outlining their main applications, advantages, and drawbacks. The article examines the assessment criteria and performance outcomes of AI-driven cybersecurity solutions. This report synthesizes previous research while identifying gaps and future prospects, including the integration of emerging AI approaches, the enhancement of real-time threat detection capabilities, and the addressing of changing attack vectors. By providing a holistic view of the current state and future potential of AI in cybersecurity, this paper aims to serve as a foundational reference for researchers and practitioners seeking to leverage AI for robust and adaptive security solutions.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3528114" target="_blank">https://dx.doi.org/10.1109/access.2025.3528114</a></p>
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identifier_str_mv 10.1109/access.2025.3528114
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/30198469
publishDate 2025
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rights_invalid_str_mv CC BY 4.0
spelling A Comprehensive Review of AI’s Current Impact and Future Prospects in CybersecurityAbdullah Al Siam (22304047)Moutaz Alazab (17730060)Albara Awajan (20083410)Nuruzzaman Faruqui (19748945)Information and computing sciencesArtificial intelligenceCybersecurity and privacyMachine learningArtificial intelligencecyber securitycyberattackmachine learningdeep learningComputer securitySecurityThreat assessmentNatural language processingReal-time systemsMalwareMachine learningElectronic mailAdaptation models<p dir="ltr">The use of artificial intelligence (AI) technology signifies a significant milestone in the swiftly evolving domain of cybersecurity. This study offers a comprehensive literature review on the role, effect, and future prospects of AI across five critical areas of cybersecurity: threat detection, endpoint security, phishing and fraud detection, network security, and adaptive authentication. The study examines contemporary developments in AI for cybersecurity, highlighting the use of these technologies to enhance security protocols. We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. Essential comparisons of AI models are presented for each area, outlining their main applications, advantages, and drawbacks. The article examines the assessment criteria and performance outcomes of AI-driven cybersecurity solutions. This report synthesizes previous research while identifying gaps and future prospects, including the integration of emerging AI approaches, the enhancement of real-time threat detection capabilities, and the addressing of changing attack vectors. By providing a holistic view of the current state and future potential of AI in cybersecurity, this paper aims to serve as a foundational reference for researchers and practitioners seeking to leverage AI for robust and adaptive security solutions.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3528114" target="_blank">https://dx.doi.org/10.1109/access.2025.3528114</a></p>2025-01-23T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2025.3528114https://figshare.com/articles/journal_contribution/A_Comprehensive_Review_of_AI_s_Current_Impact_and_Future_Prospects_in_Cybersecurity/30198469CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/301984692025-01-23T09:00:00Z
spellingShingle A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
Abdullah Al Siam (22304047)
Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Machine learning
Artificial intelligence
cyber security
cyberattack
machine learning
deep learning
Computer security
Security
Threat assessment
Natural language processing
Real-time systems
Malware
Machine learning
Electronic mail
Adaptation models
status_str publishedVersion
title A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
title_full A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
title_fullStr A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
title_full_unstemmed A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
title_short A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
title_sort A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
topic Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Machine learning
Artificial intelligence
cyber security
cyberattack
machine learning
deep learning
Computer security
Security
Threat assessment
Natural language processing
Real-time systems
Malware
Machine learning
Electronic mail
Adaptation models