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Secure Trust Evaluation Using Multipath and Referral Chain Methods

Part of the Lecture Notes in Computer Science book series (LNSC,volume 11738)

Abstract

The notions of trust and reputation have been well studied and integrated into computer networks and internet-based services, e.g., Amazon and eBay websites. Using trust and reputation as social mechanisms can enhance the quality, reliability and trustworthiness of networks or services. These social mechanisms can also be used to provide better security measures. Indeed, trust and reputation can be considered as soft security methods that compliment hard security techniques. However, data security and privacy are among the primary challenges in trust and reputation systems. We therefore propose a secure trust evaluation (STE) method in which privacy of trust values and corresponding weights are preserved. Our proposed method is constructed based on an information theoretic framework for modeling trust and two approaches that propagate trust in a network, i.e., multipath and referral chain techniques. In other words, we utilize secure multiparty computation to provide protocols by which the nodes in a network will be able to evaluate their trust values in a secure fashion. We also provide a fascinating application of our STE method in the context of network routing protocols.

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Acknowledgment

Research was sponsored by the Army Research Office and was accomplished under Grant Number W911NF-18-1-0483. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Office or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.

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Correspondence to Mohammad G. Raeini .

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Raeini, M.G., Nojoumian, M. (2019). Secure Trust Evaluation Using Multipath and Referral Chain Methods. In: Mauw, S., Conti, M. (eds) Security and Trust Management. STM 2019. Lecture Notes in Computer Science(), vol 11738. Springer, Cham. https://doi.org/10.1007/978-3-030-31511-5_8

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  • DOI: https://doi.org/10.1007/978-3-030-31511-5_8

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