A non-biased trust model for wireless mesh networks
Autor: | Maode Ma, Houda Labiod, Heng Chuan Tan, Jun Zhang, Peter Han Joo Chong |
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Rok vydání: | 2016 |
Předmět: |
021103 operations research
Wireless mesh network Computer Networks and Communications Process (engineering) Computer science media_common.quotation_subject Data_MISCELLANEOUS Pooling 0211 other engineering and technologies 020206 networking & telecommunications Regression analysis 02 engineering and technology computer.software_genre Network simulation 0202 electrical engineering electronic engineering information engineering Entropy (information theory) Data mining Electrical and Electronic Engineering Subjective logic computer Reputation media_common |
Zdroj: | International Journal of Communication Systems. 30:e3200 |
ISSN: | 1074-5351 |
Popis: | Trust models that rely on recommendation trusts are vulnerable to badmouthing and ballot-stuffing attacks. To cope with these attacks, existing trust models use different trust aggregation techniques to process the recommendation trusts and combine them with the direct trust values to form a combined trust value. However, these trust models are biased as recommendation trusts that deviate too much from one's own opinion are discarded. In this paper, we propose a non-biased trust model that considers every recommendation trusts available regardless they are good or bad. Our trust model is based on a combination of 2 techniques: the dissimilarity test and the Dempster-Shafer Theory. The dissimilarity test determines the amount of conflict between 2 trust records, whereas the Dempster-Shafer Theory assigns belief functions based on the results of the dissimilarity test. Numerical results show that our trust model is robust against reputation-based attacks when compared to trust aggregation techniques such as the linear opinion pooling, subjective logic model, entropy-based probability model, and regression analysis. In addition, our model has been extensively tested using network simulator NS-3 in an Infrastructure-based wireless mesh networks and a Hybrid-based wireless mesh networks to demonstrate that it can mitigate blackhole and grayhole attacks. |
Databáze: | OpenAIRE |
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