Trust-based data fusion mechanism design in cognitive radio networks

Wang, Ji; Chen, Ing-Ray

doi:10.1109/cns.2014.6997465

Cited by 17 publications

(14 citation statements)

References 22 publications

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“…In [24], a Stackelberg game was utilized in order to mitigate the SSDF attack to detect the corrupted nodes reports in WSNs-based CR. Meanwhile, in [36], the problem of fake inspections sent by malicious SUs in CRNs due to the SSDF was studied using static game approach to establish a statistical trust model. In [24,36], the energy detection method has been employed with game theory to detect the malicious nodes behavior due to the SSDF attack.…”

Section: Introductionmentioning

confidence: 99%

Employing Game Theory and TDMA Protocol to Enhance Security and Manage Power Consumption in WSNs-Based Cognitive Radio

Abdalzaher

Muta

2019

IEEE Access

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The rapid development of wireless sensor networks (WSNs) is the significant incentive to contribute in the vulnerable applications such as cognitive radio (CR). This paper proposes a Stackelberg game approach to enhance the WSN-based CR security against the spectrum sensing data falsification (SSDF) attack and conserve the consequent lost power consumption. The attack aims to corrupt the spectrum decision by imposing interference power to the delivered reports from the sensor nodes (SNs) to the fusion center (FC) to make a protection level below a specific threshold. The proposed model utilizes the intelligent Stackelberg game features along with the matched filter (MF) to maximize the number of protected reports sent by the SNs to the FC leading to accurate decision of the spectrum status. Furthermore, the TDMA protocol is utilized to resolve the complexity of employing MF for the spectrum detection to avoid the collision between the delivered reports. The proposed model aims to enhance the number of correctly received reports at the FC, and hence manage the lost energy of reports retransmission due to the malicious attack effect. Moreover, the model can conserve the lost power of the failure communication attempts due to the SSDF attack impact. Simulation results indicate the improved performance of the proposed protection model along with the MF over the six different environments against the SSDF attack as compared to two defense schemes, namely, random and equal weight defense strategies.In this regard, secured WSNs can dramatically contribute in CR networks (CRNs) as the fusion center (FC) needs to rely on distributed sensor nodes (SNs) to sense the spectrum status. In other words, WSNs suffer from security and power management problems specially in harsh environments. The uncontrolled WSNs security is a double defect: one is data deterioration and second is losing power consumption in transmission of designated infected data. Consequently, security in WSNs-based CR is a prominent issue that has been considered in [8,[17][18][19][20][21].One of the eminent techniques utilized in the literature to handle the security problem in WSNs is game theory [22][23][24][25][26]. Game theory is a special optimization branch which tackles the interaction among a set of rational intelligent users that aim to enhance their individual gains in an intelligent and adaptive way [27]. To this end, three main dependent challenges affecting a smooth operation for CR are spectrum sensing, mitigating security threats, and the consequent lost energy. One of the security threats in CRNs is spectrum sensing data falsification (SSDF) attack [28]. Here, the defender represents the FC. Therefore, the whole communication system in such CRN can be strictly disrupted and the network performance will be steeply degraded. In addition, this attack can disrupt the delivered reports at the FC, and hence, a wrong decision will be taken by the FC about the spectrum status. Moreover, it does not only reduce the number of correctly received reports...

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Section: Introductionmentioning

confidence: 99%

Employing Game Theory and TDMA Protocol to Enhance Security and Manage Power Consumption in WSNs-Based Cognitive Radio

Abdalzaher

Muta

2019

IEEE Access

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“…Through this reinforcement-based approach, past reports are therefore considered for the computation of decisions. Examples of schemes following this approach may be found in the collaborative sensing solutions proposed by Wang et al [20], Wang and Chen [34], and by Zeng, Paweczak, and Cabric [21]. In the former, the nodes are classified either as honest or as malicious, with all nodes initially assumed to be honest.…”

Section: Deployment Of Dedicated Trusty Sensorsmentioning

confidence: 99%

“…For instance, Min, Shin, and Hu [33] assume in their work that at least two thirds of the nodes are well behaving. On the contrary, Wang and Chen [34] propose a data fusion scheme for centralized CR networks that tolerates a high percentage of malicious SUs. This strength results from allowing the data fusion center to also sense the spectrum and use its own outcomes to assess the honesty of the SUs.…”

Section: Deployment Of Dedicated Trusty Sensorsmentioning

confidence: 99%

“…As indicated in Table 2, this approach enables the use of trust-based security schemes that may, for instance, attribute more relevance to the reports of more trustworthy SUs (e.g., through a weighted mean-based fusion scheme in which different weights are adaptively assigned to the SUs according to their reputation levels) [6,29,33,38] or ignore the sensing reports from SUs with reputation values under a defined threshold [21,34,39,40]. Globally, when a SU reports sensing data not tagged as an outlier, its reputation is increased.…”

Section: Deployment Of Dedicated Trusty Sensorsmentioning

confidence: 99%

“…Initially, only a predefined set of trusted nodes is considered reliable. Concerning the proposal of Wang and Chen [34], which also consists in a trustbased data fusion scheme, it targets centralized CR networks and aims at tolerating a high percentage of malicious SUs. We note that some authors consider that the soft-decision approach presents more potential to support the implementation of reputation-based security solutions [21].…”

Section: Deployment Of Dedicated Trusty Sensorsmentioning

confidence: 99%

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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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Trust management in cognitive radio networks: A survey

2017

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Cognitive radio is proposed to solve the interference and underutilized license problems. With the development of the cognitive functionalities, classical and new security threats become challenging. To make wireless cognitive radio networks more secure and more reliable, several approaches have been proposed in the literature. In recent years, trust and reputation management (TRM) techniques are more and more considered for cognitive radio networks to secure them against the malicious and misbehaving users that try to deprive others from using the white space. The scope of this survey is to give a comprehensive overview about the existing TRM-based mechanisms proposed for the cognitive radio networks. We expose the existing classifications of TRM techniques, then we introduce a new classification that takes into account, more exhaustively, different TRM properties and approaches.Int J Network Mgmt. 2018;28:e1999.wileyonlinelibrary.com/journal/nemThe new classification aspects are the following:1. The network topology: Every network topology may strongly affect the choice of the appropriate TRM mechanism. 2. The detection strategy: At the spectrum detection phase, the SU senses individually or cooperatively the PU activities in the channel. Each detection strategy, used to make the final decision, can be secured by different TRM mechanisms. 3. Trust computation: For each node, the trust value can be computed using intelligent or simple methods (Bayesian network, probability, etc) to distinguish between honest, suspicious, and malicious entities. 4. Spectrum management: To control the spectrum allocation and to manage the channel availability decisions, the CRN may use a centralized, distributed, or clustering spectrum sensing technique. For each spectrum management technique, different TRM approaches are proposed to secure the spectrum detection feature.The remainder of this paper is organized as follows: In section 2, we will review the security attacks and vulnerabilities in CRNs. Then, we will define, in Section 3, the concepts of the TRM. Thus, we will illustrate the existing TRM approaches and classifications. In Section 4, we will present our new classification of TRM approaches in the CRNs. CRNS ATTACKS AND VULNERABILITIESWireless networks are vulnerable to several types of attacks and threats. 2 Indeed, attacks can be classified according to the target layer. Briefly, Table 1 illustrates a list of attacks that may affect all types of wireless networks.Cognitive radio networks are vulnerable to conventional wireless networks attacks 3 but suffers further from specific attacks due to their intrinsic cognitive functionalities. In CRNs, the SUs, competing to exploit the white space, can be honest, selfish, faulty, or malicious. Faulty users may send incorrect sensing outcomes due to defective device, fading location, or shadowing zone. The erroneous spectrum detection affects the final decision and degrades the network performance. On the other hand, the selfish and malicious users aim at monopolizing the f...

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Trust-based data fusion mechanism design in cognitive radio networks

Cited by 17 publications

References 22 publications

Employing Game Theory and TDMA Protocol to Enhance Security and Manage Power Consumption in WSNs-Based Cognitive Radio

Employing Game Theory and TDMA Protocol to Enhance Security and Manage Power Consumption in WSNs-Based Cognitive Radio

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

Trust management in cognitive radio networks: A survey

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