Signaling game-based availability assessment for edge computing-assisted IoT systems with malware dissemination

Shen, Y; Shen, S; Wu, Z; Zhou, H; Yu, S

Signaling game-based availability assessment for edge computing-assisted IoT systems with malware dissemination

Shen, Y Shen, S Wu, Z Zhou, H Yu, S

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Publisher:: ELSEVIER
Publication Type:: Journal Article
Citation:: Journal of Information Security and Applications, 2022, 66
Issue Date:: 2022-05-01

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Field	Value	Language
dc.contributor.author	Shen, Y
dc.contributor.author	Shen, S
dc.contributor.author	Wu, Z
dc.contributor.author	Zhou, H
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743
dc.date.accessioned	2023-03-28T00:21:54Z
dc.date.available	2023-03-28T00:21:54Z
dc.date.issued	2022-05-01
dc.identifier.citation	Journal of Information Security and Applications, 2022, 66
dc.identifier.issn	2214-2134
dc.identifier.issn	2214-2126
dc.identifier.uri	http://hdl.handle.net/10453/168646
dc.description.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.
dc.language	English
dc.publisher	ELSEVIER
dc.relation.ispartof	Journal of Information Security and Applications
dc.relation.isbasedon	10.1016/j.jisa.2022.103140
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Signaling game-based availability assessment for edge computing-assisted IoT systems with malware dissemination
dc.type	Journal Article
utslib.citation.volume	66
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2023-03-28T00:20:57Z
pubs.publication-status	Published
pubs.volume	66

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.

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http://hdl.handle.net/10453/168646