Title

Quantifying Trust For Robust Fusion While Spectrum Sharing In Distributed Dsa Networks

Keywords

Byzantine attacks; Dynamic spectrum access; robust fusion; secure environmental sensing capability; spectrum sensing data falsification; trust and reputation

Abstract

In this paper, we quantify the trustworthiness of secondary nodes that share spectrum sensing reports in a distributed dynamic spectrum access network. We propose a spatio-spectral anomaly monitoring technique that effectively captures anomalies in the spectrum sensing reports shared by individual cognitive radio nodes. Based on this, we propose an optimistic trust model for a system with a normal risk attitude and using approximation to the Beta distribution. For a more conservative and risk averse system, we propose a multinomial Dirichlet distribution-based conservative trust framework. Using a machine learning approach, we classify malicious nodes with a high degree of certainty regardless of their aggressiveness of attacks or variations introduced by the wireless environment. Subsequently, we propose two instantaneous fusion models: 1) optimistic trust-based fusion and 2) conservative trust-based fusion, which exclude untrustworthy sensing reports from participating nodes during spectrum data fusion. Our work considers random, deterministic, and preferential (ON-OFF) attack models to demonstrate the utility of our proposed model under varied attack scenarios. Through extensive simulation experiments, we show that the trust values help identify malicious nodes with a high degree of certainty.

Publication Date

6-1-2017

Publication Title

IEEE Transactions on Cognitive Communications and Networking

Volume

3

Issue

2

Number of Pages

138-154

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/TCCN.2017.2702173

Socpus ID

85065897916 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85065897916

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