Please use this identifier to cite or link to this item:
http://dx.doi.org/10.25673/115635
Title: | Turing Machine Development for High-Secure Data Link Encoding in the Internet of Things Channel |
Author(s): | Tikhonov, Victor Taher, Abdullah Tikhonov, Serhii Shulakova, Kateryna Hluschenko, Vlad Chaika, Andrii |
Granting Institution: | Hochschule Anhalt |
Issue Date: | 2024 |
Language: | English |
Subjects: | Informationstechnik Datenverarbeitung |
Abstract: | The work considers the issues of data stream encoding in the IoT systems and networks in the context of information security provision, with particular focus on the data link layer in wireless and wired telecommunication channels. The problem state of the art shows a great progress in the sphere of IT cybersecurity based on Advanced Encryption Standard. However, new tasks and related threats emerge, such as unmanned mobile devices of mass disposable with remote control, for which known approaches are not reliable and efficient enough. In this respect, the common algorithms of data link frame encoding are studied, and original formalization of typical frames proposed for static and dynamic representation. An original method introduced for high-secure data encoding with variable frame structure. A formal grammar of an abstract Turing machine (TM) is developed for data link encoding, which is based on ternary line-signaling and three-bit command system. Constructed typical frame-patterns with the use of TM syntax. General principles are formulated for the high-secure frame encoding with variable structure for packet-based streaming on the data link layer with the use of TM algorithm. The results of the work intend to improve the mobile objects cyber-threats protection, as well as to remote vehicle control and other IoT real-time applications. |
URI: | https://opendata.uni-halle.de//handle/1981185920/117590 http://dx.doi.org/10.25673/115635 |
Open Access: | Open access publication |
License: | (CC BY-SA 4.0) Creative Commons Attribution ShareAlike 4.0 |
Appears in Collections: | International Conference on Applied Innovations in IT (ICAIIT) |
Files in This Item:
File | Description | Size | Format | |
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1_1_ICAIIT_2024_Part_2_paper_3.pdf | 1.08 MB | Adobe PDF | View/Open |