Sliding window Dixon's tests for malicious users’ suppression in a cooperative spectrum sensing system

Shrivastava, Shivanshu; Rajesh, A.; Bora, Prabin Kumar

doi:10.1049/iet-com.2013.0609

Cited by 10 publications

(10 citation statements)

References 17 publications

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“…Such an attack is similar to the false data injection attacks in smart grid cyber‐physical system . A number of mitigation strategies have been proposed, such as those reported in other works …”

Section: Introductionmentioning

confidence: 85%

“…22,23 A number of mitigation strategies have been proposed, such as those reported in other works. [24][25][26] In a PUE attack, an attacker transmits a signal with the same characteristic as the primary user signal, attempting to deceive secondary users and preventing them from accessing the available frequency spectrum. There are two typical types of attackers in such an attack, namely, a selfish attacker who seeks to maximize his/her own spectrum usage, and a malicious attacker seeking to deny secondary users from using available spectrums (ie, denial of service attacks).…”

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confidence: 99%

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A soft cooperative spectrum sensing in the presence of most destructive smart PUEA using energy detector

Emami

Zarrabi

Jabbarpour

et al. 2018

Concurrency and Computation

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Summary Recently, the growth of Internet of Things (IoT) and its remarkable impacts on human well‐being life style are deniable. On the connectivity side, IoT is highly related to Wireless Sensor Network (WSN) concept. The key elements include the data, which is machine‐produced, specifically by sensors, and the data communication through connectivity technologies. On the security side, primary user emulation attack (PUE) is one of the well‐defined attacks in cognitive radio (CR)–based WSN. Here, we investigate a smart primary user emulation attacker that has the most destructive effect on the spectrum sensing unit of cognitive radio users. To deal with this attack, a soft cooperative spectrum sensing using an energy detector is proposed. In the proposed method, the values of sensing information of each secondary user are sent to a fusion center. Once the values are received, they will be combined with some appropriate coefficients in order to minimize spectrum sensing probability of error for a given probability of false alarm. The coefficients are the variables of a constrained optimization problem. Based on simulation results, our method has a lower error probability in spectrum sensing in comparison to hard combination schemes (eg, OR rule) and soft combination schemes (eg, CSINR method).

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Section: Introductionmentioning

confidence: 85%

mentioning

confidence: 99%

A soft cooperative spectrum sensing in the presence of most destructive smart PUEA using energy detector

Emami

Zarrabi

Jabbarpour

et al. 2018

Concurrency and Computation

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show abstract

“…. , (5) if SU in at th sensing period, (6) = ∪ { , } 7end if (8) dim = dimension of (9) if dim ̸ = 0 (10) Avg ( ) = ∑ dim (11) else (12) Avg ( ) = 0 (13) end if (14) end for (15) using 25…”

Section: Evaluate the Average Of The Signal Strength Received Frommentioning

confidence: 99%

“…An SU with abnormal estimated parameters will be detected as malicious SU, and its reports will be filtered out. The authors in [14] propose applying the Dixon's test on the SUs' energy data to suppress a malicious secondary user (SU) in centralised fusion based CRNs. When the fusion center (FC) can obtain the location information of the SUs, another type of location based schemes has also been developed.…”

Section: Introductionmentioning

confidence: 99%

A Secure Cooperative Spectrum Sensing Scheme in Mobile Cognitive Radio Networks

Guo

Zhang

et al. 2014

International Journal of Distributed Sensor Networks

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The reliability of cooperative spectrum sensing (CSS) can be severely degraded by the falsified spectrum sensing reports provided by malicious secondary users (SUs). However, in existing works, the problem of secure CSS in mobile cognitive radio networks (CRNs) has not been well considered yet. The detection of abnormal sensing reports in existing works does not evaluate both sensing reports and locations of SUs simultaneously. And the mobility pattern of all SUs is assumed to be similar, which is impractical in real mobile CRNs. In this paper, spatial correlation of the received signal strength among SUs is exploited to get the evidence whether the received signal strength is consistent with the location from where it is generated. And Dempster-Shafer theory is used to filter out abnormal reports by combining the evidence collected from the spatial correlation algorithm in each sensing period. To mitigate the adverse effects caused by the SUs' mobility pattern, a fusion scheme based on SUs' reputation is proposed. In comparison to the existing schemes, simulation results demonstrate that the proposed secure CSS scheme improves the primary user detection rate by 10% at false alarm rate of 0.1 when the mobility pattern of the SUs is different.

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“…However, the limitation of the application of Dixon's test in [12] was its inefficiency in detecting multiple MUs in a CSS scheme. Further, in [13], \emph{Sliding Window Dixon's test (SW Dixon's test)} was proposed to overcome the limitations of [12]. The SW Dixon's test was found to be highly efficient in detecting multiple MUs.…”

Section: Introductionmentioning

confidence: 99%

A Sub-Optimal Low Complex Multiple Malicious Users’ Detection Mechanism in a Cooperative Spectrum Sensing System

2017

IJRTER

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In cognitive radio based cooperative sensing systems, some secondary users are likely to act malicious. Such secondary users are called malicious users. An optimal application of Dixon's outlier detection scheme for detecting malicious users in a cognitive radio cooperative spectrum sensing system has recently been termed as the Sliding Window Dixon's test. The Sliding window Dixon's test applies the Dixon's test on the smaller data sets with maximum overlaps. However, it is found that this scheme is highly complex. In this paper, we propose a novel scheme to exploit the robustness of the Dixon's test without compromising on its complexity. Simulations demonstrate that the proposed methods are efficient in suppressing multiple malicious users.

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Sliding window Dixon's tests for malicious users’ suppression in a cooperative spectrum sensing system

Cited by 10 publications

References 17 publications

A soft cooperative spectrum sensing in the presence of most destructive smart PUEA using energy detector

A soft cooperative spectrum sensing in the presence of most destructive smart PUEA using energy detector

A Secure Cooperative Spectrum Sensing Scheme in Mobile Cognitive Radio Networks

A Sub-Optimal Low Complex Multiple Malicious Users’ Detection Mechanism in a Cooperative Spectrum Sensing System

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