ANALYSIS AND OPTIMIZATION OF WAVELET DECOMPOSITION ALGORITHMS FOR USE IN REAL-TIME ANOMALY DETECTION SYSTEMS
One of the approaches to the detection of network anomalies is the analyses of parameters of functioning of a network. Characteristics, calculated on a wavelet coefficients, indeed, are more sensitive to changes in the number, than the characteristics calculated directly in a row, but this requires more calculations, the spectral-time algorithms, of course, subject to optimize for application in real-time systems. In addition, there are different approaches to the implementation of wavelet expansions, each of which has its place on the informative value (the number of qualifying ratios), the authentic values, the computational complexity of the transformations. The article offers a reasonable approach to the implementation of these algorithms for use in real-time anomaly detection systems.