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Avoiding the opportunist: the role of Simmelian ties in fostering the trust in sensor-cloud networks

Citation

Xiang, M and Liu, W and Bai, Q and Al-Anbuky, A, Avoiding the opportunist: the role of Simmelian ties in fostering the trust in sensor-cloud networks, International Journal of Distributed Sensor Networks, 2015 Article 873941. ISSN 1550-1329 (2015) [Refereed Article]


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Copyright Statement

Copyright 2015 Ming Xiang et al. This is an open access article distributed under the Creative Commons Attribution 3.0 Unported (CC BY 3.0) License, (https://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DOI: doi:10.1155/2015/873941

Abstract

The wireless sensor-cloud networks (WSCNs) are becoming popular nowadays. The new concept of trust has emerged in recent studies as an alternative mechanism to address the security concern in WSCN. Most of the studies on trust are focusing on how to model and evaluate trust so as to effectively detect any malicious activity in the network and then isolate and avoid them. In addition, WSCNs are very dynamic and flexible, thus being hard to keep a static network topology and connectivity which bring more challenges to be secured. In this paper, we have introduced the new angle of adaptive network approach to discover the interplay between network node's trust evaluation and its underlying topology change. It has been found that the network connectivity change will also have strong impact on the trust behavior running over it. Moreover, inspired from the trust studies in sociology, we propose that the Simmelian tie structured networks enable more positive impact on fostering trustworthiness among wireless sensor nodes, but the structural hole characterized networks provide more opportunity for misbehaviors and have negative impact on securing the sensor-cloud networks. The extensive simulation studies have confirmed our new concepts and validated our hypothesis.

Item Details

Item Type:Refereed Article
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Intelligent robotics
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Application software packages
UTAS Author:Bai, Q (Dr Quan Bai)
ID Code:140666
Year Published:2015
Deposited By:Information and Communication Technology
Deposited On:2020-09-01
Last Modified:2020-10-19
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