6 papers
Intelligent ARP Spoofing Detection using Multi-layered Machine Learning (ML) Techniques for IoT Networks
Anas Ali, Mubashar Husain, Peter Hans
Address Resolution Protocol (ARP) spoofing remains a critical threat to IoT networks, enabling attackers to intercept, modify, or disrupt data transmission by exploiting ARP's lack…
Optimizing Resource Allocation and Energy Efficiency in Federated Fog Computing for IoT
Taimoor Ahmad, Anas Ali
Address Resolution Protocol (ARP) spoofing attacks severely threaten Internet of Things (IoT) networks by allowing attackers to intercept, modify, or block communications. Traditio…
Optimizing Resource Allocation and Energy Efficiency in Federated Fog Computing for IoT
Syed Sarmad Shah, Anas Ali
Fog computing significantly enhances the efficiency of IoT applications by providing computation, storage, and networking resources at the edge of the network. In this paper, we pr…
Privacy-Aware Cyberterrorism Network Analysis using Graph Neural Networks and Federated Learning
Anas Ali, Mubashar Husain, Peter Hans
Cyberterrorism poses a formidable threat to digital infrastructures, with increasing reliance on encrypted, decentralized platforms that obscure threat actor activity. To address t…
Real-Time Detection of Insider Threats Using Behavioral Analytics and Deep Evidential Clustering
Anas Ali, Mubashar Husain, Peter Hans
Insider threats represent one of the most critical challenges in modern cybersecurity. These threats arise from individuals within an organization who misuse their legitimate acces…
Federated Learning-Enhanced Blockchain Framework for Privacy-Preserving Intrusion Detection in Industrial IoT
Anas Ali, Mubashar Husain, Peter Hans
Industrial Internet of Things (IIoT) systems have become integral to smart manufacturing, yet their growing connectivity has also exposed them to significant cybersecurity threats.…