Mitigation of the spectrum sensing data falsifying attack in cognitive radio networks

Rajorshi Biswas, Jie Wu, Xiaojiang Du and Yaling Yang

Cyber-Physical Systems, 2021, vol. 7, issue 3, 159-178

Abstract: Cognitive radio networks (CRNs), which offer novel network architecture for utilising spectrums, have attracted significant attention in recent years. CRN users use spectrums opportunistically, which means they sense a channel, and if it is free, they start transmitting in that channel. In cooperative spectrum sensing, a secondary user (SU) decides about the presence of the primary user (PU) based on information from other SUs. Malicious SUs (MSUs) send false sensing information to other SUs so that they make wrong decisions about the spectrum status. As a result, an SU may transmit during the presence of the PU or may keep starving for the spectrum. In this paper, we propose a reputation-based mechanism which can minimise the effects of MSUs on decision making in cooperative spectrum sensing. Some of the SUs are selected as distributed fusion centres (DFCs), that are responsible for making decisions about the presence of PU and informing the reporting SUs. A DFC uses weighted majority voting among the reporting SUs, where weights are normalised reputation. The DFC updates reputations of SUs based on confidence of an election. If the majority wins by a significant margin, the confidence of the election is high. In this case, SUs that belong to the majority gain high reputations. We conduct extensive simulations to validate our proposed model.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/23335777.2020.1811387 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tcybxx:v:7:y:2021:i:3:p:159-178

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tcyb20

DOI: 10.1080/23335777.2020.1811387

Access Statistics for this article

Cyber-Physical Systems is currently edited by Yang Xiao

More articles in Cyber-Physical Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().