CAMNEP: agent-based network intrusion detection system

We present a prototype of agent-based intrusion detection system designed for deployment on high-speed backbone networks. The main contribution of the system is the integration of several anomaly detection techniques by means of collective trust modeling within a group of collaborative detection agents, each featuring a specific detection algorithm. The anomalies are used as an input for the trust modeling. In this stage, each agent determines the flow trustfulness from aggregated anomalies. The aggregation is performed by extended trust models that model the trustfulness of generalized situated identities, represented by a set of observable features. The system is based on traffic statistics in NetFlow format acquired by dedicated hardware-accelerated network cards, and is able to perform a real-time surveillance of the gigabit networks.