Are professionals of information security, within the framework of which the processes of formation, functioning and evolution of cyber objects are studied, to identify sources of cyber-danger formed while determining their characteristics, as well as their classification and formation of regulatory documents, implementation of security systems in future.
Published in Chapter:
Machine Learning Application With Avatar-Based Management Security to Reduce Cyber Threat
Vardan Mkrttchian (HHH University, Australia), Leyla Gamidullaeva (Penza State University, Russia & K. G. Razumovsky Moscow State University of Technologies and Management, Russia), Yulia Vertakova (Southwest State University, Russia), and Svetlana Panasenko (Plekhanov Russian University of Economics, Russia)
Copyright: © 2019
|Pages: 16
DOI: 10.4018/978-1-5225-8100-0.ch005
Abstract
This chapter is devoted to studying the opportunities of machine learning with avatar-based management techniques aimed at optimizing threat for cyber security professionals. The authors of the chapter developed a triangular scheme of machine learning, which included at each vertex one participant: a trainee, training, and an expert. To realize the goal set by the authors, an intelligent agent is included in the triangular scheme. The authors developed the innovation tools using intelligent visualization techniques for big data analytic with avatar-based management in sliding mode introduced by V. Mkrttchian in his books and chapters published by IGI Global in 2017-18. The developed algorithm, in contrast to the well-known, uses a three-loop feedback system that regulates the current state of the program depending on the user's actions, virtual state, and the status of implementation of available hardware resources. The algorithm of automatic situational selection of interactive software component configuration in virtual machine learning environment in intelligent-analytic platforms was developed.