CatchIt: Detect Malicious Nodes in Collaborative Spectrum Sensing

Wang, Wenkai; Li, Husheng; Sun, Yan; Han, Zhu

doi:10.1109/glocom.2009.5425380

Cited by 87 publications

(60 citation statements)

References 13 publications

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“…Similarly, we get equations (14) and (15), by differentiating ln Λ γ and ln Λ ρ , and equating them to 0. To ensure that the likelihood is positive, ρ has to lie in the interval (0, 1/(K L + 1)).…”

Section: Ss S ∈ H and N (S)mentioning

confidence: 99%

“…For instance, in [11], the primary user emulation attack was described and a transmitter verification scheme was proposed to distinguish a primary user from other sources; [12] discussed the attack where malicious users attempted to mislead the learning process of secondary users; denial-of-service attacks were considered and potential protection remedies were discussed in [13]; in [14], a malicious user reporting false sensing results would be found and excluded from the collaborative spectrum sensing when the calculated "suspicious" level was high; in [15], an information secrecy game was developed to foster collaboration between primary users and secondary users against eavesdroppers.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Anti-Jamming Games in Multi-Channel Cognitive Radio Networks

Wang

Liu

et al. 2012

IEEE J. Select. Areas Commun.

218

146

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Abstract-Crucial to the successful deployment of cognitive radio networks, security issues have begun to receive research interests recently. In this paper, we focus on defending against the jamming attack, one of the major threats to cognitive radio networks. Secondary users can exploit the flexible access to multiple channels as the means of anti-jamming defense. We first investigate the situation where a secondary user can access only one channel at a time and hop among different channels, and model it as an anti-jamming game. Analyzing the interaction between the secondary user and attackers, we derive a channel hopping defense strategy using the Markov decision process approach with the assumption of perfect knowledge, and then propose two learning schemes for secondary users to gain knowledge of adversaries to handle cases without perfect knowledge. In addition, we extend to the scenario where secondary users can access all available channels simultaneously, and redefine the anti-jamming game with randomized power allocation as the defense strategy. We derive the Nash equilibrium for this Colonel Blotto game which minimizes the worst-case damage. Finally, simulation results are presented to verify the performance.

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Section: Ss S ∈ H and N (S)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Anti-Jamming Games in Multi-Channel Cognitive Radio Networks

Wang

Liu

et al. 2012

IEEE J. Select. Areas Commun.

218

146

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“…For example, statistics-based anomaly detection has been proposed [12], [14], [17], [18]. Chen et al [12] proposed a sensor reputation management framework that assigns different weights to sensing reports based on their reputation achieved from a previous sensing history.…”

Section: Related Workmentioning

confidence: 99%

Robust cooperative sensing via state estimation in cognitive radio networks

Min

Kim²,

Shin

2011

2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)

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Abstract-Cooperative sensing, a key enabling technology for dynamic spectrum access, is vulnerable to various sensingtargeted attacks, such as the primary user emulation or spectrum sensing data falsification. These attacks can easily disrupt the primary signal detection process, thus crippling the operation of dynamic spectrum access. While such sensing-targeted attacks can be easily launched by an attacker, it is very challenging to design a robust cooperative spectrum sensing scheme due mainly to the practical constraints inherent in spectrum sensing, particularly the shared/open nature of the wireless medium and the unpredictability of signal propagation. In this paper, we develop an efficient, yet simple attack detection framework, called IRIS (robust cooperatIve sensing via iteRatIve State estimation), that safeguards the incumbent detection process by checking the consistency among sensing reports via the estimation of system states, namely, the primary user's transmit-power and pathloss exponent. The key insight behind the design of IRIS is that the sensing results are governed by the network topology and the law of signal propagation, which cannot be easily compromised by an attacker. Consequently, the sensing reports must demonstrate consistency among themselves in estimating system states. Our analytical and simulation results show that, by performing consistency-checks, IRIS provides high attackdetection capability, and preserves satisfactory performance in estimating the system states even under very challenging attack scenarios. Based on these observations, we propose a new incumbent detection rule that can further improve the spectrum efficiency. IRIS can be readily deployed in infrastructure-based cognitive radio networks, such as IEEE 802.22 WRANs, with manageable processing and communication overheads.

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“…Existing research on SSDF attacks often assume the existence of a fusion center that collects local measurements and makes the final decision of whether primary users are present or absent [2], [6], [8]- [12]. They also assume that a common control channel for information exchange in the protocol.…”

Section: Introductionmentioning

confidence: 99%

ReDiSen: Reputation-based secure cooperative sensing in distributed cognitive radio networks

Zhang

Safavi–Naini

2013

2013 IEEE International Conference on Communications (ICC)

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Abstract-Cognitive radio techniques represent an emerging approach for mitigating the spectrum scarcity problem in wireless communications. Cooperative sensing is an effective solution to improve sensing accuracy and robustness in the presence of fading and shadowing that make individual sensing less reliable. However, when an adversary can corrupt some nodes in the network, the effectiveness of cooperative sensing may degrade dramatically. We design the first fully distributed security scheme ReDiSen to counter attacks in cooperative sensing. We apply reputation generated from exchanged sensing results as an aid to restrict the impact of the malicious behaviours. Both theoretical analysis and simulation results indicate that ReDiSen provides an effective countermeasure against security attacks by enabling secondary users to obtain more accurate cooperative sensing results in adversarial environments. ReDiSen does not rely on a central authority, nor a common control channel, and is therefore more applicable in dynamic cognitive radio networks.

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CatchIt: Detect Malicious Nodes in Collaborative Spectrum Sensing

Cited by 87 publications

References 13 publications

Anti-Jamming Games in Multi-Channel Cognitive Radio Networks

Anti-Jamming Games in Multi-Channel Cognitive Radio Networks

Robust cooperative sensing via state estimation in cognitive radio networks

ReDiSen: Reputation-based secure cooperative sensing in distributed cognitive radio networks

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