Publications

Selected research publications and contributions

"Deep Q-ICAN: A Deep Reinforcement Learning-based Approach for Real-time CPA Attack Detection and Mitigation in NDN Architecture"

Computer Networks, 2025

This paper presents Deep Q-ICAN, a novel deep reinforcement learning approach for real-time detection and mitigation of Cache Pollution Attacks in Named Data Networking architecture, achieving 98% cache hit ratio and 98.87% detection accuracy.

Deep Learning NDN Security Reinforcement Learning Cache Pollution

"Improving NDN Resilience: A Novel Mitigation Mechanism Against Cache Pollution Attack"

2024 International Wireless Communications and Mobile Computing (IWCMC), IEEE, 2024

This research proposes a novel mitigation mechanism to improve Named Data Networking resilience against cache pollution attacks, enhancing network performance and security in wireless communications environments.

NDN Wireless Communications Attack Mitigation Network Resilience

"Q-ICAN: A Q-learning based Cache Pollution Attack Mitigation Approach for Named Data Networking"

Computer Networks, Vol. 235, 2023

This paper introduces Q-ICAN, an intelligent Q-learning based technique for detecting and mitigating cache pollution attacks in NDN, achieving 95.09% accuracy rate and 94% cache hit ratio while reducing average retrieval delay by 18%.

Q-Learning NDN Security Cache Pollution Machine Learning