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Symmetry
Special Issues
Complex Systems Modeling Using Graphs and Symmetry/Asymmetry
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Complex Systems Modeling Using Graphs and Symmetry/Asymmetry

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Mathematics".

Deadline for manuscript submissions: closed (10 April 2023) | Viewed by 1686

Special Issue Editor

Prof. Dr. Dmitry Zegzhda

E-Mail Website
Guest Editor
Institute of Cybersecurity, Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, room 172, St. Petersburg 195251, Russia
Interests: information security of cyber-physical systems; automatic process control systems and the Internet of Things; security of operating systems; security of artificial intelligence and machine learning

Special Issue Information

Dear Colleagues,

Graph theory is the most versatile and powerful mechanism for representing a variety of systems for solving problems of modeling properties, their structure and behavior dynamics. This mathematical tool makes it possible to formalize the general laws of the functioning and development of complex and dynamic systems in all advanced fields, including cybernetics, telecommunications, biology, materials science, social sciences, and economics.

In this regard, the proposed Special Issue contains the results of research in a wide variety of areas. However, the general aim lies in modeling the characteristics of complex systems, formalizing their structures and general patterns of their development, optimizing the processes occurring in them, researching algorithms for their control and self-organization based on graph theory and the properties of their symmetry/asymmetry.

Prof. Dr. Dmitry Zegzhda
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • graph theory
  • graph invariants
  • symmetric graphs
  • fractal graphs
  • structures stability
  • interconnection networks
  • multi-agent systems
  • algorithms on graphs
  • structures optimization
  • structural synthesis
  • self-similarity
  • self-regulation
  • symmetric encryption
  • adaptation
  • evolutionary cybernetics
  • situational control
  • functional systems theory
  • emerging sensor network (ESN)

Published Papers (1 paper)

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Research

13 pages, 495 KiB  
Article
Application of the Learning Automaton Model for Ensuring Cyber Resiliency
by Maxim Kalinin, Tigran Ovasapyan and Maria Poltavtseva
Symmetry 2022, 14(10), 2208; https://0-doi-org.brum.beds.ac.uk/10.3390/sym14102208 - 20 Oct 2022
Cited by 2 | Viewed by 1618
Abstract
This work addresses the functional approach to ensuring cyber resiliency as a kind of adaptive security management. For this purpose, we propose a learning automaton model capable of self-learning and adapting to changes while interacting with the external environment. Each node in the [...] Read more.
This work addresses the functional approach to ensuring cyber resiliency as a kind of adaptive security management. For this purpose, we propose a learning automaton model capable of self-learning and adapting to changes while interacting with the external environment. Each node in the under-controlled system has a set of probable actions with respect to neighboring nodes. The same actions are represented in the graph of the learning automaton, but the probabilities of actions in the graph model are permanently updated based on the received reinforcement signals. Due to the adaptive reconfiguration of the nodes, the system is able to counteract the cyberattacks, preserving resiliency. The experimental study results for the emulated wireless sensor network (WSN) are presented and discussed. The packets loss rate stays below 20% when the number of malicious nodes is 20% of the total number of nodes, while the common system loses more than 70% of packets. The network uptime with the proposed solution is 30% longer; the legitimate nodes detect malicious nodes and rebuild their interaction with them, thereby saving their energy. The proposed mechanism allows ensuring the security and functional sustainability of the protected system regardless of its complexity and mission. Full article
(This article belongs to the Special Issue Complex Systems Modeling Using Graphs and Symmetry/Asymmetry)
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