A Systematic Literature Review on AI-Based Methods and Challenges in Detecting Zero-Day Attacks Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.1109/access.2024.3455410
The detection of zero-day attacks remains one of the most critical challenges in cybersecurity. This systematic literature review focuses on the various AI-based methods employed for detecting zero-day attacks, identifying both the strengths and weaknesses of these approaches. By critically evaluating existing literature, this review provides new insights and highlights the gaps that future research must address. The findings suggest that while artificial intelligence, particularly machine learning, offers promising solutions, there are significant challenges related to data availability, algorithmic complexity, and real-time application. This review contributes to the field by providing a comprehensive analysis of current AI-driven methods and proposing future research directions to enhance zero-day attack detection.
Related Topics
- Type
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- Language
- en
- Landing Page
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- OA Status
- gold
- Cited By
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4402301350Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2024.3455410Digital Object Identifier
- Title
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A Systematic Literature Review on AI-Based Methods and Challenges in Detecting Zero-Day AttacksWork title
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articleOpenAlex work type
- Language
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enPrimary language
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2024Year of publication
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2024-01-01Full publication date if available
- Authors
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Lip Yee Por, Zhen Dai, Siew Juan Leem, Yi Chen, Jing Yang, Farid Binbeshr, Koo Yuen Phan, Chin Soon KuList of authors in order
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https://doi.org/10.1109/access.2024.3455410Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1109/access.2024.3455410Direct OA link when available
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Computer science, Systematic review, MEDLINE, Law, Political scienceTop concepts (fields/topics) attached by OpenAlex
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25Total citation count in OpenAlex
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2025: 23, 2024: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W1095282497, https://openalex.org/W4309997699, https://openalex.org/W4385415883, https://openalex.org/W3160345471, https://openalex.org/W3119729076, https://openalex.org/W4394699061, https://openalex.org/W4393305240, https://openalex.org/W4210954769, https://openalex.org/W3033764928, https://openalex.org/W3200723554, https://openalex.org/W3184395191, https://openalex.org/W4388905985, https://openalex.org/W4295036743, https://openalex.org/W3128286744, https://openalex.org/W4393115034, https://openalex.org/W4389833619, https://openalex.org/W3185153723, https://openalex.org/W4293386228, https://openalex.org/W2805511146, https://openalex.org/W4391947125, https://openalex.org/W4224249813, https://openalex.org/W4391409156, https://openalex.org/W4367309662, https://openalex.org/W2747715470, https://openalex.org/W3176551042, https://openalex.org/W3026804104, https://openalex.org/W4353004226, https://openalex.org/W1152223117, https://openalex.org/W4391503438, https://openalex.org/W4312277152, https://openalex.org/W4319737964, https://openalex.org/W4367296576, https://openalex.org/W4391069478, https://openalex.org/W4311415244, https://openalex.org/W3162364548, https://openalex.org/W4367281759, https://openalex.org/W4392246839, https://openalex.org/W4387327976, https://openalex.org/W4392452933, https://openalex.org/W4391069054, https://openalex.org/W3047793363, https://openalex.org/W2959428502, https://openalex.org/W3162527267, https://openalex.org/W3120918731, https://openalex.org/W4312234998, https://openalex.org/W4386575225, https://openalex.org/W4293578035, https://openalex.org/W4385488666, https://openalex.org/W6779770935, https://openalex.org/W4387142683, https://openalex.org/W2064675550, https://openalex.org/W2800557391, https://openalex.org/W4319777588 |
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