On adversarial attack detection in the artificial intelligence era: Fundamentals, a taxonomy, and a review
The rapid advancement and sophisticated deployment of artificial intelligence tools by malicious actors have led to the rise of highly complex cyber-attacks that evolve quickly. This rapid evolution has made traditional defense systems increasingly ineffective at detecting and mitigating these hidde...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-09-01
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| Series: | Intelligent Systems with Applications |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667305325000808 |
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| author | Noora Al Roken Hakim Hacid Ahmed Bouridane Abir Hussain |
| author_facet | Noora Al Roken Hakim Hacid Ahmed Bouridane Abir Hussain |
| author_sort | Noora Al Roken |
| collection | DOAJ |
| description | The rapid advancement and sophisticated deployment of artificial intelligence tools by malicious actors have led to the rise of highly complex cyber-attacks that evolve quickly. This rapid evolution has made traditional defense systems increasingly ineffective at detecting and mitigating these hidden threats. Adversarial attacks are a prime example of such sophisticated cyber-attacks; they subtly alter attack patterns to evade detection by intelligent systems while still maintaining their harmful functionality. This paper provides a comprehensive overview of computer malware, examining both traditional concealment methods and more advanced adversarial techniques. It includes an in-depth analysis of recent research efforts aimed at detecting previously unseen adversarial attacks using both traditional and AI-driven approaches. Furthermore, this study discusses the limitations of current network intrusion detection systems and proposes directions for future research. |
| format | Article |
| id | doaj-art-0e76fbd4c7dc4a53b00f8fe0d824ff45 |
| institution | Matheson Library |
| issn | 2667-3053 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Intelligent Systems with Applications |
| spelling | doaj-art-0e76fbd4c7dc4a53b00f8fe0d824ff452025-07-11T04:31:58ZengElsevierIntelligent Systems with Applications2667-30532025-09-0127200554On adversarial attack detection in the artificial intelligence era: Fundamentals, a taxonomy, and a reviewNoora Al Roken0Hakim Hacid1Ahmed Bouridane2Abir Hussain3Department of Electrical Engineering, University of Sharjah, Sharjah, United Arab Emirates; Department of Computer Engineering, University of Sharjah, Sharjah, United Arab Emirates; Corresponding authors.Technology Innovation Intitute, Abu Dhabi, 5500, United Arab EmiratesDepartment of Computer Engineering, University of Sharjah, Sharjah, United Arab EmiratesDepartment of Electrical Engineering, University of Sharjah, Sharjah, United Arab Emirates; Corresponding authors.The rapid advancement and sophisticated deployment of artificial intelligence tools by malicious actors have led to the rise of highly complex cyber-attacks that evolve quickly. This rapid evolution has made traditional defense systems increasingly ineffective at detecting and mitigating these hidden threats. Adversarial attacks are a prime example of such sophisticated cyber-attacks; they subtly alter attack patterns to evade detection by intelligent systems while still maintaining their harmful functionality. This paper provides a comprehensive overview of computer malware, examining both traditional concealment methods and more advanced adversarial techniques. It includes an in-depth analysis of recent research efforts aimed at detecting previously unseen adversarial attacks using both traditional and AI-driven approaches. Furthermore, this study discusses the limitations of current network intrusion detection systems and proposes directions for future research.http://www.sciencedirect.com/science/article/pii/S2667305325000808Adversarial learningAdversarial attackCyberattacksCybersecurityNetwork intrusion detection |
| spellingShingle | Noora Al Roken Hakim Hacid Ahmed Bouridane Abir Hussain On adversarial attack detection in the artificial intelligence era: Fundamentals, a taxonomy, and a review Intelligent Systems with Applications Adversarial learning Adversarial attack Cyberattacks Cybersecurity Network intrusion detection |
| title | On adversarial attack detection in the artificial intelligence era: Fundamentals, a taxonomy, and a review |
| title_full | On adversarial attack detection in the artificial intelligence era: Fundamentals, a taxonomy, and a review |
| title_fullStr | On adversarial attack detection in the artificial intelligence era: Fundamentals, a taxonomy, and a review |
| title_full_unstemmed | On adversarial attack detection in the artificial intelligence era: Fundamentals, a taxonomy, and a review |
| title_short | On adversarial attack detection in the artificial intelligence era: Fundamentals, a taxonomy, and a review |
| title_sort | on adversarial attack detection in the artificial intelligence era fundamentals a taxonomy and a review |
| topic | Adversarial learning Adversarial attack Cyberattacks Cybersecurity Network intrusion detection |
| url | http://www.sciencedirect.com/science/article/pii/S2667305325000808 |
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