Applying Change Point Detection Technique to Dynamically Support Network Security

Internet of Things applications open up attractive prospects in various areas of human activity. At the same time, the ubiquity and adoption of IoT technologies is constrained by fears of potential threats to which new technologies are vulnerable. The concept of radio overcomes the problem of lack of resources, especially for IoT edge devices. However, cognitive radio networks are vulnerable to specific intrusions due to the unique cognitive characteristics of these networks. Both machine learning-based intrusion detection and sequential statistical analysis can be effectively used by intrusion detection systems, and in some cases, statistical sequential analysis is preferable. This paper discusses change point detection methods and how they can be used to support cognitive radio system security.