Noryusliza Abdullah

Tun Hussein Onn University of Malaysia

Papers

1

Total Citations

18

H-Index

1

About

Noryusliza Abdullah is a cybersecurity researcher whose work focuses on the critical challenge of defending network infrastructure against large-scale flooding attacks. She is best known for her pioneering research on adaptive detection and prevention models for Distributed Denial of Service (DDoS) attacks and flash crowd events—two phenomena that can cripple online services. Her most cited paper, "An Adaptive Model for Detection and Prevention of DDoS and Flash Crowd Flooding Attacks" (2018), has garnered 18 citations, establishing her as a thoughtful voice in network security. In this work, Abdullah proposed a multi-agent system that intelligently distinguishes between malicious DDoS traffic and legitimate flash crowds, a notoriously difficult problem in real-time network defense. Her research integrates software agents, feature extraction, and adaptive algorithms to create more resilient security frameworks. Beyond this flagship study, Abdullah’s broader interests span mobile ad hoc networks, robot vision, and Java-based security implementations. Her contributions are particularly valuable for students and researchers working at the intersection of multi-agent systems and cybersecurity, offering practical, adaptive solutions to one of the most persistent threats in the digital age.

Research Focus

Key Achievements

1
H-Index
1
Papers
18
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
An Adaptive Model for Detection and Prevention of DDoS and Flash Crowd Flooding Attacks
18 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Tun Hussein Onn University of Malaysia

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago