Zhou, B, Maines, CL, Tang, SOT, Shi, Q, Yang, P, Yang, Q and Qi, J (2018) A 3D Security Modelling Platform for Social IoT Environments. IEEE Transactions on Computational Social Systems, 5 (4). pp. 1174-1188. ISSN 2329-924X
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Abstract
Social IoT environment comprises not just smart devices, but also the humans to interact with these IoT devices. The benefits of such system are overshadowed by the issues of cyber security. A new approach is required for us to understand the security implication under such dynamic environment, while taking both the social and technical aspects into consideration. This paper proposed a 3D security modelling platform that can capture and model security requirements in Social IoT environment. The modelling process is graphical notation based, working as a security extension to Business Process Model and Notation. Still, it utilises the latest 3D game technology thus the security extensions are generated through the third dimension. In this way, the introduction of security extensions will not increase the complexity of the original SIoT scenario, while keeping all the key information in the same platform. Together with the security ontology we have proposed, these comprehensive security notations created a unique platform that aiming at addressing the ever complicated security issues in SIoT envorinment.
Item Type: | Article |
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Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Computer Science & Mathematics |
Publisher: | Institute of Electrical and Electronics Engineers |
Date Deposited: | 23 Oct 2018 07:58 |
Last Modified: | 04 Sep 2021 10:00 |
URI: | https://researchonline.ljmu.ac.uk/id/eprint/9519 |
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