nach oben

Automatic Control and Computer Sciences

Erschienen in:

01.12.2018

The Use of Adjacency Series for Recognition of Prefractal Graphs in Assessing VANET Cybersecurity

verfasst von: P. D. Zegzhda, D. V. Ivanov, D. A. Moskvin, A. A. Ivanov

Erschienen in: Automatic Control and Computer Sciences | Ausgabe 8/2018

Einloggen, um Zugang zu erhalten

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract—

This paper considers the possibility of using prefractal graph theory to ensure information security of Vehicular ad hoc Networks (VANETs) and describes prefractal graph recognition algorithms developed for this purpose.

Nächster Artikel Hierarchical Software-Defined Security Management for Large-Scale Dynamic Networks

Moerov, A.S. and Bel’fer, R.A., Security of self-organizing automobile networks VANET, Elektrosvyaz’, 2012, no. 3.

Moerov, A.S. and Bel’fer, R.A., An information security risk assessment model for the VANET network based on the theory of fuzzy sets, Molodezhnyi Nauchno-Tekh. Vestn. Akad. Inzh. Nauk im. A. M. Prokhorova, 2013, no. 10, p. 47.

Gohale, V., Gosh, S.K., and Gupta, A., Classification of attacks on wireless mobile ad hoc networks and vehicular ad hoc networks, in Security of Self-Organizing Networks: MANET, WSN, WMN, VANET, 2011.

Zegzhda, D.P., Sustainability as a criterion for information security in cyber-physical systems, Autom. Control Comput. Sci., 2016, vol. 50, no. 8, pp. 813–819.CrossRef

Semenov, A.S., Fractal evolutionary architectures, Upr. Bol’shimi Sist., 2010, no. 30-1, pp. 91–103.

Kochkarov, A.A. and Kochkarov, R.A., On planarity and other topological properties of fractal graphs, Preprint of Inst. Appl. Math., Russ. Acad. Sci., Moscow, 2003.

Reznikov, A.V., Study of the properties and recognition of prefractal graphs, Cand. Sci. (Phys.-Math.) Dissertation, Demidov Yaroslavl State University, 2013.

Titel: The Use of Adjacency Series for Recognition of Prefractal Graphs in Assessing VANET Cybersecurity
verfasst von: P. D. Zegzhda
D. V. Ivanov
D. A. Moskvin
A. A. Ivanov
Publikationsdatum: 01.12.2018
Verlag: Pleiades Publishing
Erschienen in: Automatic Control and Computer Sciences / Ausgabe 8/2018
Print ISSN: 0146-4116
Elektronische ISSN: 1558-108X
DOI: https://doi.org/10.3103/S0146411618080266

Neuer Inhalt

Bildnachweise

VDI-Icon, Profil Icon, inhalt2, Springer Professional Modul/© Springer Fachmedien Wiesbaden GmbH, Zukunftswerkstatt Sales Excellence_ieS/© Springer Fachmedien Wiesbaden GmbH, Search Icon, Banner Hanser, Bunte Männchen, die Kunden darstelle, werden von einem riesigen Magneten angezogen. /© Oleksiy Mark, Dr. Daniel Schneider/© Fraunhofer IESE, Interview Level Ten PPA Bild/© LevelTen, Zeitschrift Wissensmanagement Cover, PatentFit-Logo/© Springer Fachmedien Wiesbaden GmbH, Zukunftswerkstatt Sales Excellence 2024/© AndreyPopov / Getty Images / iStock, 2023_Antrieb/© supervisuell, ATZ-Webinar: Prototypenfreie Entwicklung durch Offline- und Driver-in-the-Loop-HiL-Tests /© (c) VI-grade

Springer Professional

Abstract—

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Weitere Artikel der Ausgabe 8/2018

Studying the Effect of Selection of the Sign and Ratio in the Formation of a Signature in a Program Identification Problem

Modification of Preliminary Blom’s Key Distribution Scheme Taking into Account Simplex Channels

An Approach to the Programs Security Analysis using Vector Representation of Machine Code

Security Analysis Based on Controlling Dependences of Network Traffic Parameters by Wavelet Transformation

Detection of Threats in Cyberphysical Systems Based on Deep Learning Methods Using Multidimensional Time Series

Security Provision in Wireless Sensor Networks on the Basis of the Trust Model

Neuer Inhalt

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.