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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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Intelligent Systems with Applications |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667305325000808 |
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| Summary: | 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. |
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| ISSN: | 2667-3053 |