Abnormal traffic detection in networks of the Internet of things based on fuzzy logical inference

The paper proposes a traffic anomaly detection technique which could be implemented in networks of the Internet of things. It is based on using fuzzy logical inference applied to the stationary Poisson or self-similar traffic peculiar to networks of the Internet of things. The algorithms of the modified stochastic approximation and "sliding window", included in the traffic anomaly detection technique, are suggested. Results of an experimental assessment of the technique are discussed.