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PSTRM: Privacy-aware sociopsychological trust and reputation model for wireless sensor networks

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Abstract

The high possibility of attack is greatly attributed to the broadcast nature of the communication medium in which the sensor nodes operate; this makes eavesdropping of messages possible on the network. This paper proposes a privacy-aware sociopsychological trust and reputation management (PSTRM) model. The paper presents a model that models the ability of a node as a continuum based on the current battery level and outage probability of the network. PSTRM also utilise an Elliptic-Curve Cryptography Diffie-Hellman (ECCDH) privacy-aware dissemination framework which encourages the sharing of accurate and credible indirect reputation information within network neighbourhoods. The following social constructs, viz., ability, benevolence and consistency were considered in the design of the proposed model. The detection rate of the proposed model was evaluated against that by Rathore et al., using MATLAB. PSTRM was found to have high detection rates than the proposal by Rathore et al.

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Authors and Affiliations

  1. Department of Computer Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    Henry Nunoo-Mensah & Kwame Osei Boateng

  2. Department of Telecommunication Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    James Dzisi Gadze

Authors
  1. Henry Nunoo-Mensah
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  2. Kwame Osei Boateng
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  3. James Dzisi Gadze
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Correspondence to Henry Nunoo-Mensah.

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Nunoo-Mensah, H., Boateng, K.O. & Gadze, J.D. PSTRM: Privacy-aware sociopsychological trust and reputation model for wireless sensor networks. Peer-to-Peer Netw. Appl. 13, 1505–1525 (2020). https://doi.org/10.1007/s12083-020-00906-5

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