A Security Data Forwarding Mechanism for Sparse Social Sensor Networks

Xin Guan
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Xin Guan: School of Information Science and Technology, Heilongjiang University, Harbin, Heilongjiang 150080, China

International Journal of Distributed Sensor Networks, 2015, vol. 11, issue 8, 931080

Abstract: With the development of the Internet of Things (IoTs), various sensor networks were deployed to sense and collect data anytime and anywhere. Traditional sparse social sensor networks (SSSNs) assume that nodes are willing to help others with packet forwarding. However, real application scenarios, such as civilian SSSNs, often observe selfish behaviors. Therefore, the assumption that nodes are cooperative is not realistic in all applications. Currently, most of the existing incentive mechanisms focus on individual selfish behaviors. Little research work has addressed social selfish behavior in SSSNs. In this paper, we propose to incentivize nodes to cooperate with others by using a virtual bank mechanism. This incentive mechanism can effectively avoid individual selfish behaviors. This mechanism, however, renders unfair social distribution. That is, poverty nodes would appear in the networks and become internal threats for social SSSNs. To avoid this, we introduce the Gini coefficient to measure the inequality of the social distribution. Furthermore, by using the taxation strategy, we avoid the internal threats caused by social selfishness. To demonstrate the selfish behavior, we introduce the forwarding protocol which is based on social relations of nodes. We demonstrate the viability of our proposed methods through extensive simulation evaluations.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:11:y:2015:i:8:p:931080

DOI: 10.1155/2015/931080

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