Network Anomaly Detection Based on Artificial Immune System for Industrial Internet of Things

The paper analyzes the relevance of ensuring the security of wireless sensor networks (WSN), proposes the use of an artificial immune system (AIS) to detect anomalies in such networks. A dataset on WSN connections called WSN-DS was used to train and evaluate the efficiency of proposed system. Computational experiments were conducted with the use of the cosine distance, Euclidean measure and Hamming distance in the AIS. The system demonstrated the highest efficiency when using Hamming distance measure.

Hali tarjima qilinmagan