Shen, Yizhou, Shen, Shigen, Wu, Zongda, Zhou, Haiping and Yu, Shui 2022. Signaling game-based availability assessment for edge computing-assisted IoT systems with malware dissemination. Journal of Information Security and Applications 66 , 103140. 10.1016/j.jisa.2022.103140 |
Abstract
IoT malware dissemination seriously exacerbates the decline of IoT system availability, which deteriorates the users experience. To address the issue, we first predict the optimal IoT malware dissemination strategy based on a signaling game for edge computing-assisted IoT systems. We then develop an algorithm to obtain the solution of the signaling IoT availability assessment game, which is to factually reflect IoT malware dissemination in practice and reasonably express the probability of IoT system nodes being successfully infected by malware. Thus, a state transition diagram of IoT system nodes can be further designed, illustrating intercommunication among all six states during IoT malware dissemination. Upon this state transition diagram, we represent the state transition probability of IoT system nodes in each state utilizing a Markov matrix, and attain the steady-state availability of an IoT system node from reliability theory. Consequently, we deduce metrics to access the steady-state availability of the entire IoT system under typical star-, tree-, and mesh topologies, respectively. We also design the corresponding IoT system availability assessment algorithm from the view of practice. In this manner, an availability assessment mechanism for edge computing-based IoT systems with malware dissemination is constructed. Experiments demonstrate the influence of IoT system features on predicting IoT malware dissemination probability and assessing the steady-state availability of three typical IoT system topologies. Our results can be utilized to lay a theoretical foundation for guiding the implementation of higher availability for edge computing-assisted IoT systems with malware dissemination.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Publisher: | Elsevier |
ISSN: | 2214-2126 |
Last Modified: | 10 Feb 2024 02:23 |
URI: | https://orca.cardiff.ac.uk/id/eprint/148402 |
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