Defense Against SSDF Attack in Cognitive Radio Networks: Attack-Aware Collaborative Spectrum Sensing Approach

Sharifi, Abbas Ali; Niya, Javad Musevi

doi:10.1109/lcomm.2015.2499286

Cited by 52 publications

(24 citation statements)

References 9 publications

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“…Of the various existing security threats, SSDF and PUEA are very common and draw much attention to the research community. Efforts have been made to detect and defend against these attacks …”

Section: Related Work On Security In Cssmentioning

confidence: 99%

Joint cooperative spectrum sensing and primary user emulation attack detection in cognitive radio networks using fuzzy conditional entropy maximization

Banerjee

Maity

2019

Trans Emerging Tel Tech

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Cooperative spectrum sensing (CSS) in cognitive radio system shows improved performance on spectrum sensing but, at the same time, faces a common threat called primary user emulation attack (PUEA) that impersonates the primary user (PU). This work explores joint PU and PUEA detection on CSS as a multiclass hypothesis using fuzzy conditional entropy maximization. To meet the goal, a multithreshold approach is suggested using a constrained differential evolution algorithm search to determine an optimal set of fuzzy function parameters, which maximizes the conditional entropy on the energy values. The proposed work also investigates the performance of CSS in presence of a group of malicious users (as PUEA), which generates signals and directly sends the same to the fusion center. Numerical results through simulation illustrate the efficacy of the proposed scheme in terms of both reliable PU detection in presence or absence of PUEA/malicious user and separate detection of falsifying PU and energy consumption in CSS. Simulation results show that the proposed scheme offers ∼17.54% and ∼39.39% higher detection probability of PU over the existing works in presence of PUEA.

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Section: Related Work On Security In Cssmentioning

confidence: 99%

Joint cooperative spectrum sensing and primary user emulation attack detection in cognitive radio networks using fuzzy conditional entropy maximization

Banerjee

Maity

2019

Trans Emerging Tel Tech

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“…The communication channel between the CR users and FC is assumed to be an error-free reporting channel. The probabilities of PU signal detection and false alarm are computed by (5) where (. ) Q is the tail probability of standard normal distribution.…”

Section: System Model and Energy Detection Schemementioning

confidence: 99%

“…During SSDF attacks, CR attackers send falsified spectrum sensing results to the FC and disrupt the global sensing decision. To overcome the impact of SSDF attacks, several different solutions have been proposed in previously [5][6][7]. In PUEA, a malicious attacker mimics some characteristics of the legitimate PU's signal.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Threshold Selection Approach in Voting Rule for Detection of Primary User Emulation Attack

Sharifi¹,

Mofarreh-Bonab²

2018

Electrica

Self Cite

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Cognitive radio (CR) technology presents a mechanism for efficient spectrum usage. Spectrum sensing is an essential CR function which includes an intelligent signal processing algorithm to identify the vacant frequency bands. Cooperative spectrum sensing (CSS) has been widely adopted to improve the performance of CR networks. Unfortunately, CR networks are vulnerable to security threats. In this study, we propose an optimal threshold selection approach to address one of the most important attacks called primary user emulation attack (PUEA). In PUEA, a malicious attacker mimics some important primary signal features and deceives CR sensors to prevent them from accessing the available channels. In this study, we assume a malicious PUEA which is relatively located near the potential user (PU) transmitter and senses the spectrum and accurately detects the vacant frequency bands to transmit its fake signal. We estimate attack strength and then apply the K-out-of-N rule to obtain an optimum and dynamic threshold K, minimizing the global error probability. Here, the attack strength is defined as the ratio of the average transmission power of the PUEA to the average power of the PU. The achieved simulation results indicate that the performance of the suggested method is satisfactory in detecting the malicious PUEA compared with conventional methods.

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“…It includes four consecutive procedures, which are (1) basic probability assignment (BPA) with this approach, (2) holistic credibility calculation, (3) option and amelioration for BPA, and (4) evidence combination via the D-S rule, respectively [15]. In [16], a new method was proposed, which estimated the attack strength and applies it in the k−out−N rule to obtain the optimum value of k that minimizes the Bayes risk.…”

Section: Introductionmentioning

confidence: 99%

A Double Adaptive Approach to Tackle Malicious Users in Cognitive Radio Networks

Khan

Jibran

Koo

et al. 2019

Wireless Communications and Mobile Computing

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Cognitive radio (CR) is being considered as a vital technology to provide solution to spectrum scarcity in next generation network, by efficiently utilizing the vacant spectrum of the licensed users. Cooperative spectrum sensing in cognitive radio network has a promising performance compared to the individual sensing. However, the existence of the malicious users’ attack highly degrades the performance of the cognitive radio networks by sending falsified data also known as spectrum sensing data falsification (SSDF) to the fusion center. In this paper, we propose a double adaptive thresholding technique in order to differentiate legitimate users from doubtful and malicious users. Prior to the double adaptive approach, the maximal ratio combining (MRC) scheme is utilized to assign weight to each user such that the legitimate users experience higher weights than the malicious users. Double adaptive threshold is applied to give a fair chance to the doubtful users to ensure their credibility. A doubtful user that fails the double adaptive threshold test is declared as a malicious user. The results of the legitimate users are combined at the fusion center by utilizing Dempster-Shafer (DS) evidence theory. Effectiveness of the proposed scheme is proved through simulations by comparing with the existing schemes.

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Defense Against SSDF Attack in Cognitive Radio Networks: Attack-Aware Collaborative Spectrum Sensing Approach

Cited by 52 publications

References 9 publications

Joint cooperative spectrum sensing and primary user emulation attack detection in cognitive radio networks using fuzzy conditional entropy maximization

Joint cooperative spectrum sensing and primary user emulation attack detection in cognitive radio networks using fuzzy conditional entropy maximization

Dynamic Threshold Selection Approach in Voting Rule for Detection of Primary User Emulation Attack

A Double Adaptive Approach to Tackle Malicious Users in Cognitive Radio Networks

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