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Proceedings ArticleDOI

Robust Distributed Spectrum Sensing in Cognitive Radio Networks

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TLDR
This work proposes a new data fusion technique that uses a variable number of samples, and introduces a reputation-based mechanism to the Sequential Probability Ratio Test (SPRT), which is evaluated by comparing it with a variety of data fusion techniques under various network operating conditions.
Abstract
Distributed spectrum sensing (DSS) enables a Cognitive Radio (CR) network to reliably detect licensed users and avoid causing interference to licensed communications. The data fusion technique is a key component of DSS. We discuss the Byzantine failure problem in the context of data fusion, which may be caused by either malfunctioning sensing terminals or Spectrum Sensing Data Falsification (SSDF) attacks. In either case, incorrect spectrum sensing data will be reported to a data collector which can lead to the distortion of data fusion outputs. We investigate various data fusion techniques, focusing on their robustness against Byzantine failures. In contrast to existing data fusion techniques that use a fixed number of samples, we propose a new technique that uses a variable number of samples. The proposed technique, which we call Weighted Sequential Probability Ratio Test (WSPRT), introduces a reputation-based mechanism to the Sequential Probability Ratio Test (SPRT). We evaluate WSPRT by comparing it with a variety of data fusion techniques under various network operating conditions. Our simulation results indicate that WSPRT is the most robust against the Byzantine failure problem among the data fusion techniques that were considered.

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Citations
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Cooperative spectrum sensing for cognitive radio networks

TL;DR: A parallel fusion based cooperat iv sensing network, in which the sensors send their sensing information to an access provider, which makes the final decision regarding presence or absence of the primary signal, is considered.

A Survey on Security and Privacy Protocols for Cognitive Wireless Sensor Networks

TL;DR: In this paper, the authors present a comprehensive discussion on various security issues in cognitive wireless sensor networks (CWSNs) by identifying numerous security threats in these networks and defense mechanisms to counter them.
Proceedings ArticleDOI

A Regression Based Spectrum-Sensing Data - Falsification Attack Detection Technique in CWSN

TL;DR: A new algorithm for dynamic spectrum sensing and spectrum allocation in Cognitive wireless sensor networks (CWSNs), the Maximum-Match Filtering algorithm (MMF) is proposed, executed at the base station to counter the Spectrum Sensing Data Falsification attack.
Posted Content

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Proceedings ArticleDOI

Extra-sensing game for malicious primary user emulator attack in cognitive radio network

TL;DR: The problem can be formulated as a zero-sum game to modeling and analyzing the strategies for two players and the results show that the benefit ratio and the probability of channel's availability strongly influence the equilibrium.
References
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Book

Wireless Communications: Principles and Practice

TL;DR: WireWireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design as discussed by the authors, which covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs).
Journal ArticleDOI

Cognitive radio: brain-empowered wireless communications

TL;DR: Following the discussion of interference temperature as a new metric for the quantification and management of interference, the paper addresses three fundamental cognitive tasks: radio-scene analysis, channel-state estimation and predictive modeling, and the emergent behavior of cognitive radio.

Cognitive Radio An Integrated Agent Architecture for Software Defined Radio

Joseph Mitola
TL;DR: This article briefly reviews the basic concepts about cognitive radio CR, and the need for software-defined radios is underlined and the most important notions used for such.
Proceedings ArticleDOI

Implementation issues in spectrum sensing for cognitive radios

TL;DR: To improve radio sensitivity of the sensing function through processing gain, three digital signal processing techniques are investigated: matched filtering, energy detection and cyclostationary feature detection.
Proceedings ArticleDOI

Collaborative spectrum sensing for opportunistic access in fading environments

TL;DR: This paper studies spectrum-sharing between a primary licensee and a group of secondary users and suggests that collaboration may improve sensing performance significantly.
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