Detection of Traffic Anomalies Based on Their Frame Wavelet Transformations Processing

Relevance. The active transition to a massive digital infrastructure based on Internet of Things (IoT) technology has brought telecommunications networks to the level of dominant information resources. The one-time increase in the number of existing Internet services is inextricably linked to the growing variety of network anomalies on telecommunications equipment. In turn, existing methods of detecting network threats do not allow timely assessment of network traffic, which is characterized by a large number of parameters, and the detected anomalies from external interference do not have pronounced patterns. The purpose of the study is to increase the efficiency of detecting traffic anomalies based on the results of processing its frame wavelet transform. The scientific task is to develop scientific and methodological approaches that allow effective analysis and timely detection of anomalies in network traffic. A comparative review of search methods for detecting network traffic anomalies, algorithms for detecting uncontrolled anomalies, traffic analysis methods based on local emission factor, binary trees, optical emission spectroscopy. Decision. The results of the study of the possibility of detecting anomalies in the bitstream traffic based on the results of its multiple-variable transformation in the Haar wavelet basis are considered. The choice for further processing of the coefficients of the traffic decomposition matrix along the time shift variable is justified. It is proved that multiple-scale transformations not only increase the structural differences in traffic, but also open up the possibility of localization of anomalies that caused these differences. The scientific novelty of the work is determined by the author's approach to detecting network traffic anomalies during the transition from the direct representation of a signal in the form of its discrete samples to coefficients formed from the matrices of its wavelet transformations, and, as a result, increasing its contrast with other signals with a similar structure. Theoretical significance. The necessity and sufficiency of using wavelet coefficients instead of time samples of signals in the basis of the parent wavelet from the matrix of the generated frame is proved. The relationship between the Hurst indicators and the coefficients of the cross-correlation functions has been established. Practical significance. The results obtained in the work, in the future, can be used in the construction of models for evaluating network traffic in conditions of deliberate, as well as methods for searching and synthesizing effective methods of protection against them.

traffic anomalies, detection of bit stream anomalies, statistical traffic parameters, localization of the position of anomalies in the traffic structure