Detecting Primary User Emulation Attacks in Dynamic Spectrum Access Networks

Jin, Zilong; Anand, S.; Subbalakshmi, K. P.

doi:10.1109/icc.2009.5198911

Cited by 135 publications

(75 citation statements)

References 13 publications

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“…However, they employ a mono-criterion, the received signal strength, to infer distance and analyze the presence of a PUE in the CRN. As in [7], other works have employed a unique criterion to analyze the presence of PUE attacks [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Resilient and multi-dimensional cooperative spectrum sensing on cognitive radio networks

Soto

Nogueira

Chowdhury

2013

2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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Abstract-While great strides have been made in spectrum sensing techniques in cognitive radio networks, these approaches are susceptible to unconventional attacks that may result in catastrophic performance degradation of the spectrum usage efficiency. For example, primary user emulation, intelligent jamming and denial of service for spectrum usage may impact the performance of classical spectrum sensing approaches. To address these challenges, this paper proposes a multi-dimensional cooperative sensing framework that can flexibly incorporate a variety of physical layer features to identify cases related to malicious behavior and genuine node failures. Though our approach is distributed, it is resilient in the sense that it does not simply rely on majority voting by a collection of nearby nodes. The key contributions of this paper are as follows: (i) A multiple criteria analysis technique and a non-parametric Bayesian inference method are formulated for identifying the spectrum holes that are least susceptible to malicious activity and failures, and (ii) Using real traces from the CRAWDAD data repository, we test our framework in a variety of practical settings, to prove the performance benefit of our approach.

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Section: Introductionmentioning

confidence: 99%

Resilient and multi-dimensional cooperative spectrum sensing on cognitive radio networks

Soto

Nogueira

Chowdhury

2013

2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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“…Based on the expressions of µ i , λ i and π, we can see that they are also independent of p j i . Thus, according to Eqn (19), U m s is independent of p j i . That is, as the system reaches steady state, the net payoff of malicious nodes does not depend on their switching probabilities.…”

Section: B Markov Model Analysismentioning

confidence: 99%

“…Based on the induction hypothesis, U k s follows the Eqn (19), and so C 1 = 0. We now write U k+1 s as:…”

Section: B Markov Model Analysismentioning

confidence: 99%

“…However, these localization mechanisms require a dedicated sensor network which may not be available in practical distributed DSA networks. Jin et al [18], [19] proposed a hypothesis based approach to mitigate PUE attacks using an analytical model for the received power at the secondary users without assuming any prior knowledge about the position of either the malicious or the secondary users. The first analytical model for the received power was proposed in [20].…”

Section: Related Workmentioning

confidence: 99%

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Analysis of Coordinated Denial-of-Service Attacks in IEEE 802.22 Networks

Tan

Sengupta

Subbalakshmi

2011

IEEE J. Select. Areas Commun.

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Abstract-The cognitive radio enabled IEEE 802.22 wireless regional area network (WRAN) is designed to opportunistically utilize the unused or under-utilized TV bands. However, due to the open paradigm of cognitive radio networks and lack of proactive security protocols, the IEEE 802.22 networks are vulnerable to various denial-of-service (DoS) threats. In this paper, we study the coordinated DoS attacks on IEEE 802.22 networks from the malicious users' perspective. We formulate this problem from both a one-stage and a multi-stage scenario. In the one-stage scenario, we formulate a cooperative game among the malicious nodes and derive the optimal decision strategy for the them. In the multi-stage case, we propose a discretetime Markov chain model for the dynamic behavior of both malicious nodes and the 802.22 secondary networks. Simulation and numerical results demonstrate that in the one-stage case, the coordinated attack achieves 10-15% improvement compared to the non-cooperative attack from the perspective of malicious nodes, and, in the multi-stage case, there exists an optimal number of malicious nodes participating in the attack for the steady system to maximize the net payoff.

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“…They disturb the transmission by generating signal same as that of secondary user. The attack caused by generating the signal same as that of primary user is called Primary User Emulation Attack (PUEA) [2].…”

Section: Introductionmentioning

confidence: 99%

Detection of PUE Attack by SPARS Model using WSPRT

Sairam¹,

Ramakrishnaiah²

2015

IJSEA

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Cognitive radio is a system which improves the utilization of the spectrum by sensing the white spaces in its vicinity. This sensed information will be utilized by the Secondary User (SU) to transmit the data. But some of the malicious users attacks th system by generating the signal same as that of the primary transmitter. The attack caused by generating the signal same as t primary transmitter is called as Primary User Emulation Attack (PUEA). In this paper the Signal Activity Pattern Acquisition Reconstruction System (SPARS) is used to detect the attack. But this system suffers from low True Positive Rate. To incr positive rate or sensitivity a new technique was proposed called as Weighted Sequential Probability Ratio Test (WSPRT). By improving the true positive rate or sensitivity, the detection capability of the system will be improved.

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Detecting Primary User Emulation Attacks in Dynamic Spectrum Access Networks

Cited by 135 publications

References 13 publications

Resilient and multi-dimensional cooperative spectrum sensing on cognitive radio networks

Resilient and multi-dimensional cooperative spectrum sensing on cognitive radio networks

Analysis of Coordinated Denial-of-Service Attacks in IEEE 802.22 Networks

Detection of PUE Attack by SPARS Model using WSPRT

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