Real-time detection of intrusive traffic in QoS network domains
Abdulghani Ali Ahmed, Aman Jantan, Tat‐Chee Wan · IEEE Security & Privacy · 2013
A capable, scalable, and reliable model detects intrusive traffic by investigating the impact of user behavior on quality-of-service regulations in real time. The model also proposes reliable coordination for investigating user traffic, including traffic injected through several gateways. Traffic investigation is triggered only when the network is congested; at that moment, burst gateways generate an echo of explicit congestion notification to misbehaving users. The model investigates these users by measuring their bandwidth consumption ratios. User traffic that exceeds the service-level agreement bandwidth ratio is filtered as intrusive. Simulation results demonstrate that the proposed model efficiently monitors user behavior and detects intrusive traffic.