CFAR Intrusion Detection Method Based on Network Flow Prediction Model
Wei Hong-jun · Information Security and Communications Privacy · 2008
Constant false alarm rate(CFAR) intrusion detection method based on network flow prediction is proposed in this paper. The network flow can be predicted by using the AR model, and an appropriate detection threshold is chosen through the CFAR in radar signal processing, which can decide whether an intrusion signal exists or not. According to the simulations based on the DARPA datasets of Lincoln Lab, different CFAR detections are compared and analyzed. Finally, the united CFAR detection is proposed, which shows that the detective probability is actively high while the false alarm rate fairly low.