Distributed Intelligent System of Network Traffic Anomaly Detection Based on Artificial Immune System

The paper analyzes the essence of intrusion detection systems, identifies the relevance of detecting unknown attacks with a low number of False Positives, and identifies the significant parameters of the NSL-KDD dataset network connections. The authors have developed a distributed system for detecting network anomalies, using the mechanisms of an artificial immune system. A series of computational experiments was conducted that demonstrated a high level of efficiency of the developed system and a low percentage of False Positives.