Abstract
The literature review of known sources forming the theoretical basis of calculations on Sleptsova networks and on the basis of authors' developments in machine learning with avatar-based management established the basis for the future solutions to hyper-computations to support cyber security applications. The chapter established that the petri net performed exponentially slower and is a special case of the Sleptsov network. The universal network of Sleptsov is a prototype of the Sleptsov network processor. The authors conclude that machine learning with avatar-based management at the platform of the Sleptsov net-processor is the future solution for cyber security applications in Russia.
TopBackground
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
Shareable Content Object Reference Model (SCORM): Is a collection of standards and specifications for web-based electronic educational technology (also called e-learning).
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.
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.
Sleptsov Net (SN): Is a bipartite directed multi-graph supplied with a dynamic process.