Modeling of adaptive recognition of cyberattacks in a non-uniform flow of requests in e-business modules - Лахно, Валерій Анатолійович; Петренко, Тарас Анатолійович; Пирог, Микола Володимирович (Ukrainian Scientific Journal of Information Security, 2016)
The rapid development of modern information society, in particular, distribution systems, e-business and e-commerce (CEB) in vari-ous sectors of the economy, has caused some problems with the provision of cyber security, and accordingly, the development of the market anomaly detection systems, cyberattacks and threats that identify illegitimate action attacking side. Existing classic intrusion detection systems, suffer from a number of significant deficiencies, which imposes restrictions on their practical use. Now there is a trend of growth in demand for intelligent security technology of cyberspace, capable of simulating cognitive processes and are based on machine learning and pattern recognition theory. Hence, we need further research to develop the methodological and theoretical foundations of information synthesis cyber defense systems capable of self-learning. A mathematical model of adaptive functioning of cyberattacks recognition system (AСRS) at a non-uniform flow of network requests and cyber classes in CEB. It was found that the Markov process models are widely used in the analysis and synthesis of AСRS, the Markov property is a certain limitation on the real signals, but it is sufficient for the development of methods of content analysis and synthesis AСRS complexes. It was determined that the mathematical models using Markov chain device is an effective tool for quantitative assessment and recognition of complex cyberattacks with non-uniform flow of requests in AСRS.