Conceptualizing Trust: A Typology and E-Commerce Customer Relationships Model
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 7 - Volume 7
Beyond proof-of-compliance: security analysis in trust management
Journal of the ACM (JACM)
Proceedings of the 3rd international conference on Embedded networked sensor systems
VigilNet: An integrated sensor network system for energy-efficient surveillance
ACM Transactions on Sensor Networks (TOSN)
DRBTS: Distributed Reputation-based Beacon Trust System
DASC '06 Proceedings of the 2nd IEEE International Symposium on Dependable, Autonomic and Secure Computing
Real-Time Detection of Clone Attacks in Wireless Sensor Networks
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
Towards pre-standardization of trust and reputation models for distributed and heterogeneous systems
Computer Standards & Interfaces
Trust management systems for wireless sensor networks: Best practices
Computer Communications
Inferring and mitigating a link's hindering transmissions in managed 802.11 wireless networks
Proceedings of the sixteenth annual international conference on Mobile computing and networking
Multicast performance with hierarchical cooperation
IEEE/ACM Transactions on Networking (TON)
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As many wireless sensor networks (WSNs) are deployed in complicated environment without good physical protection, the sensor nodes are more vulnerable to be affected by uncertain factors from inside or outside so that the sensed data always cannot reflect the real world situation well. Thus the trustworthiness of sensor nodes should be evaluated for revising the faulty ones in after-deployment maintenances. In this paper, we propose a trustworthiness evaluation method based on D-S evidence theory in data level for sensor nodes which can sense multi-dimensional data. Different dimensions of a sensor node are regarded as its different trustworthiness attributes in this method. For a single node, the trustworthiness of each attribute is evaluated firstly based on evidence theory, and then the lower and upper limits of trust degree for this node are calculated by fusing the evaluation results of different attributes. Moreover, in order to figure out whether regional uncertain factors exist or not, the trust degree of a local region is given by fusing the judgments of deployed sensor nodes according to the combination rules of evidence theory. Extensive experiments based on actual data samples are conducted to evaluate the performance of our method. The theoretical analysis and experimental results show that our method can give effective trustworthiness evaluation for one single sensor node or a local region. Also, robustness and stability of this method are verified in the experiments.