Machine Learning and Cyber Security: Future Potential of the Research

Machine Learning and Cyber Security: Future Potential of the Research

Vardan Mkrttchian (HHH University, Australia), Sergey Kanarev (Penza State University, Russia) and Leyla Ayvarovna Gamidullaeva (Penza State University, Russia)
Copyright: © 2020 |Pages: 9
DOI: 10.4018/978-1-5225-9715-5.ch070
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Cybersecurity has become an important subject of national, international, economic, and social importance that affects multiple nations. The literature review of known sources is forming theoretical bases of calculations on Sleptsov networks. The universal network of Sleptsov is a prototype of the Sleptsov network processor. The authors in the article research the emerging trends and theoretical perspectives of cyber security development using machine-learning technique with avatar-based management at the platform of Sleptsov net-processor and propose further prospects for development of hyper-computation.
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Many researchers compare machine learning solutions for cyber security by considering one specific application (e.g., Buczak and Guven, 2016; Blanzieri and Bryl, 2008; Gardiner and Nagaraja, 2016) and are typically oriented to Artificial Intelligence experts.

The term “cyber security” refers to three things:

  • 1.

    A set of activities and other measures, technical and non-technical, intended to protect computers, computer networks, related hardware devices and software, and the information they contain and communicate, including software and data, as well as other elements of cyberspace, from all threats, including threats to national security;

  • 2.

    The degree of protection resulting from the application of these activities and measures;

  • 3.

    The associated field of professional endeavor, including research and analysis, aimed at implementing those activities and improving their quality (Jenab, et al., 2018).

At the same time, our previous research of the problem of cyber security showed that cyber security is a section of information security, within the framework of which the processes of formation, functioning and evolution of cyber objects are studied. It is necessary 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. However, working on the application of the machine learning for Cyber Security applications with the use of developed by the authors Avatars-Based Management techniques, we came to the conclusion that this is not so, and the built-in cyber security systems can be destroyed by the same artificial intelligence.

Key Terms in this Chapter

Sleptsov Net (SN): Is a bipartite directed multi-graph supplied with a dynamic process.

Hypercomputation or Super-Turing Computation: Is a multi-disciplinary research area with relevance across a wide variety of fields, including computer science, philosophy, physics, electronics, biology, and artificial intelligence; models of computation that can provide outputs that are not Turing computable.

Machine Learning Application With Avatar-Based Management Technique Use: Is a class of methods of natural intelligence, the characteristic feature of which is not a direct solution of the problem but training in the process of applying solutions to a set of similar problems.

Machine Learning: Is the use of artificial intelligence (AI) that provides systems with the capability to learn and automatically improve from experience (data) without being explicitly programmed.

Shareable Content Object Reference Model (SCORM): Is a collection of standards and specifications for web-based electronic educational technology (also called e-learning).

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