Defeating Primary User Emulation Attacks Using Belief Propagation in Cognitive Radio Networks

Zhou, Yuan; Niyato, Dusit; Li, Husheng; Song, Ju Bin; Han, Zhu

doi:10.1109/jsac.2012.121102

Cited by 97 publications

(59 citation statements)

References 24 publications

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“…We must also consider the possibility of attackers being able to predict which channels will be used by the SUs and emulate PU activity on those specific channels, increasing significantly the effectiveness of the attacks [44]. In fact, a PU emulation attack can result in a DoS attack to a legitimate SU when the attacker has enough intelligence to transmit a fake signal on the selected channel any time that SU performs sensing [45].…”

Section: Primary User Emulation In Cr Environmentsmentioning

confidence: 99%

“…Most existing proposals address the detection of PU emulation attacks by estimation of the location of the transmitters and comparing it with the a priori known locations of the legitimate PUs, as in IEEE 802.22 through the access to geo-location databases [5,6,43,44,48,49]. If the estimated location of an emitter deviates from the known locations of the PUs, then the likelihood of this being a PU emulation attacker increases.…”

Section: Location-and Distance-based Approachesmentioning

confidence: 99%

“…Idoudi, Daimi, and Saed [53] state that existing solutions against PU emulation attacks do not handle PU and SU mobility appropriately. For example, Yuan et al [44] only consider the possibility of television transmitters in their proposal, i.e., PUs with fixed and known PU locations. The cooperative solution that is proposed by León, Hernández-Serrano, and Soriano [54], which specifically targets centralized IEEE 802.22 networks, is based on the same assumption and thus cannot cope with the emulation of PUs that have unknown locations (e.g., wireless microphones), despite its ability to precisely determine the locations of received signals.…”

Section: Location-and Distance-based Approachesmentioning

confidence: 99%

See 2 more Smart Citations

A survey on security attacks and countermeasures with primary user detection in cognitive radio networks

Marinho

Granjal

Monteiro

2015

EURASIP J. on Info. Security

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Currently, there are several ongoing efforts for the definition of new regulation policies, paradigms, and technologies aiming a more efficient usage of the radio spectrum. In this context, cognitive radio (CR) emerges as one of the most promising players by enabling the dynamic access to vacant frequency bands on a non-interference basis. However, the intrinsic characteristic of CR opens new ways for attackers, namely in the context of the effective detection of incumbent or primary users (PUs), the most fundamental and challenging requirement for the successful operation of CR networks. In this article, we provide a global and integrated vision of the main threats affecting CR environments in the context of the detection of primary users, with a particular focus on spectrum sensing data falsification and primary user emulation attacks. We also address solutions and research challenges still required to address such threats. Our discussion aims at being complete and self-contained, while also targeting readers with no specific background on this important topic of CR environments. It is, as far as our knowledge goes, the first work providing a global and clear vision of security threats and countermeasures in the context of primary user detection in CR.

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Section: Primary User Emulation In Cr Environmentsmentioning

confidence: 99%

Section: Location-and Distance-based Approachesmentioning

confidence: 99%

Section: Location-and Distance-based Approachesmentioning

confidence: 99%

See 1 more Smart Citation

A survey on security attacks and countermeasures with primary user detection in cognitive radio networks

Marinho

Granjal

Monteiro

2015

EURASIP J. on Info. Security

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“…In PUE, an attacker can simulate a signal that resembles the signal of the PU, thereby misleading the SU [2,12,18,58,[69][70][71][72][73]. In this case, the attacker has a chance to focus on the physical layer, pretending to be an authorised user by sending CR signals that are similar to PU signals, allowing them to deceive other SUs.…”

Section: ) Security In Spectrum Sensingmentioning

confidence: 99%

Spectrum Sharing Security and Attacks in CRNs: a Review

Alhakami¹,

Mansour²,

Safdar³

2014

IJACSA

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Abstract-Cognitive Radio plays a major part in communication technology by resolving the shortage of the spectrum through usage of dynamic spectrum access and artificial intelligence characteristics. The element of spectrum sharing in cognitive radio is a fundamental approach in utilising free channels. Cooperatively communicating cognitive radio devices use the common control channel of the cognitive radio medium access control to achieve spectrum sharing. Thus, the common control channel and consequently spectrum sharing security are vital to ensuring security in the subsequent data communication among cognitive radio nodes. In addition to well known security problems in wireless networks, cognitive radio networks introduce new classes of security threats and challenges, such as licensed user emulation attacks in spectrum sensing and misbehaviours in the common control channel transactions, which degrade the overall network operation and performance. This review paper briefly presents the known threats and attacks in wireless networks before it looks into the concept of cognitive radio and its main functionality. The paper then mainly focuses on spectrum sharing security and its related challenges. Since spectrum sharing is enabled through usage of the common control channel, more attention is paid to the security of the common control channel by looking into its security threats as well as protection and detection mechanisms. Finally, the pros and cons as well as the comparisons of different CR-specific security mechanisms are presented with some open research issues and challenges.

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“…By evaluating the received signal's coverage area [4], [5] or channel characteristics [6], [7], one can differentiate between the signal from a PUE attacker This material is based upon work supported by the National Science Foundation (NSF) CAREER award under Grant Number (CNS-1149500), and co-supported by NSF under Grant Number 1002113. and the real TV signal. However, these detection techniques cannot be applied to detect the attack that emulates WM signals, named WM user emulation (WMUE) attack, because both locations and channel characteristics of legitimate WM systems are hard to acquire and validate.…”

Section: Introductionmentioning

confidence: 99%

Detecting multi-channel wireless microphone user emulation attacks in white space with noise

Zeng

Richardson

et al. 2013

8th International Conference on Cognitive Radio Oriented Wireless Networks

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Abstract-In this work, we study a special kind of primary user emulation (PUE) attack, named wireless microphone user emulation (WMUE) attack in white space cognitive radio networks. In WMUE attacks, a malicious user emulates wireless microphone (WM) signals in order to block secondary users. Existing work on WMUE attack detection deals with single channel senario. Although multi-channel WM (MCWM) systems are common, detecting WMUE attacks under a multi-channel setting in noisy environments has not been well studied and the existing solution for single channel case cannot be directly applied. In a practical multi-channel WM system, the audio signals on different channels mix with each other and are contaminated by noises, which introduce great challenges on WMUE attack detection. We propose a novel multi-channel WMUE attack detection scheme which is based on the crosscorrelation between the demodulated FM signal and the acoustic signal. The audio interferences, audio noises, and RF noises are all resisted by the cross-correlation. To reduce computation complexity, we propose a 1.5-bit FM demodulator whose outputs are represented by only 0, 1 and -1. Moreover, we set up a MCWM system and developped a hardware based prototype to evaluate the performance of the proposed scheme. Experimental results show that, the proposed scheme can effectively detect multi-channel WMUE attacks within 0.25 second with detection rate larger than 0.9 and false alarm rate lower than 0.1 under low signal-to-noise ratios.

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Defeating Primary User Emulation Attacks Using Belief Propagation in Cognitive Radio Networks

Cited by 97 publications

References 24 publications

A survey on security attacks and countermeasures with primary user detection in cognitive radio networks

A survey on security attacks and countermeasures with primary user detection in cognitive radio networks

Spectrum Sharing Security and Attacks in CRNs: a Review

Detecting multi-channel wireless microphone user emulation attacks in white space with noise

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