AI & DEEP LEARNING-BASED ANOMALY DETECTION FOR DDOS MITIGATION IN MODERN NETWORKS Article Swipe
Distributed Denial of Service (DDoS) attacks pose a significant threat to online systems by overwhelming target servers with illegitimate traffic. Traditional signature-based detection methods struggle with evolving attack patterns. This paper proposes the use of Artificial Intelligence (AI) and deep learning techniques—particularly Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN)—to analyze network traffic and detect anomalous behaviors in real time. The results demonstrate the effectiveness of deep learning models in identifying complex and zero-day DDoS attacks with high accuracy and minimal false positives.
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Metadata
- Type
- book-chapter
- Language
- en
- Landing Page
- https://doi.org/10.26524/royal.239.28
- https://www.royalbookpublishing.com/index.php/royal/catalog/download/533/569/2170
- OA Status
- hybrid
- References
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4412068440Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.26524/royal.239.28Digital Object Identifier
- Title
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AI & DEEP LEARNING-BASED ANOMALY DETECTION FOR DDOS MITIGATION IN MODERN NETWORKSWork title
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book-chapterOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-07-07Full publication date if available
- Authors
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Michael Mahesh KList of authors in order
- Landing page
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https://doi.org/10.26524/royal.239.28Publisher landing page
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https://www.royalbookpublishing.com/index.php/royal/catalog/download/533/569/2170Direct link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://www.royalbookpublishing.com/index.php/royal/catalog/download/533/569/2170Direct OA link when available
- Concepts
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Denial-of-service attack, Anomaly detection, Deep learning, Artificial intelligence, Computer science, World Wide Web, The InternetTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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2Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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