2024
DOI: 10.1049/cmu2.12736
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Knowledge graph reasoning for cyber attack detection

Ezekia Gilliard,
Jinshuo Liu,
Ahmed Abubakar Aliyu

Abstract: In today's digital landscape, cybercriminals are constantly evolving their tactics, making it challenging for traditional cybersecurity methods to keep up. To address this issue, this study explores the potential of knowledge graph reasoning as a more adaptable and sophisticated approach to identify and counter network attacks. By leveraging graph structures imbued with human‐like thinking, this method enhances the resilience of cybersecurity systems. The study focuses on three critical aspects: data preparati… Show more

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Cited by 2 publications
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“…Additionally, we recommend investigating promising research directions for SDN-based data centers, such as AI-driven network management, Federated Learning for Decentralized SDN, cybersecurity considerations, and scalability and performance improvements. 22,23 These efforts will contribute to the ongoing evolution of data center networking, improving flexibility, programmability, and overall efficiency in network operations.…”
Section: Discussionmentioning
confidence: 99%
“…Additionally, we recommend investigating promising research directions for SDN-based data centers, such as AI-driven network management, Federated Learning for Decentralized SDN, cybersecurity considerations, and scalability and performance improvements. 22,23 These efforts will contribute to the ongoing evolution of data center networking, improving flexibility, programmability, and overall efficiency in network operations.…”
Section: Discussionmentioning
confidence: 99%