Reputation-Based Spectrum Sensing Strategy Selection in Cognitive Radio Ad Hoc Networks

Sun, Zhiguo; Xu, Zhenyu; Chen, Zengmao; Ning, Xiaoyan; Guo, Lili

doi:10.3390/s18124377

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…In [8], the FC allocates a reasonable weight value (depending on historical sensing behavior of nodes) according to the submitted observations' evaluation to make the global decision. In [9], an algorithm was proposed by Z. Sun et al to select better sensing strategies either collaboratively or independently.…”

Section: Related Workmentioning

confidence: 99%

Throughput and Interference for Cooperative Spectrum Sensing: A Malicious Perspective

2021

KSII TIIS

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Cognitive radio (CR) is a feasible intelligent technology and can be used as an effective solution to spectrum scarcity and underutilization. As the key function of CR, cooperative spectrum sensing (CSS) is able to effectively prevent the harmful interference with primary users (PUs) and identify the available spectrum resources by exploiting the spatial diversity of multiple secondary users (SUs). However, the open nature of the cognitive radio networks (CRNs) framework makes CSS face many security threats, such as, the malicious user (MU) launches Byzantine attack to undermine CRNs. For this aim, we make an in-depth analysis of the motive and purpose from the MU's perspective in the interweave CR system, aiming to provide the future guideline for defense strategies. First, we formulate a dynamic Byzantine attack model by analyzing Byzantine behaviors in the process of CSS. On the basis of this, we further make an investigation on the condition of making the fusion center (FC) blind when the fusion rule is unknown for the MU. Moreover, the throughput and interference to the primary network are taken into consideration to evaluate the impact of Byzantine attack on the interweave CR system, and then analyze the optimal strategy of Byzantine attack when the fusion rule is known. Finally, theoretical proofs and simulation results verify the correctness and effectiveness of analyses about the impact of Byzantine attack strategy on the throughput and interference.

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Section: Related Workmentioning

confidence: 99%

Throughput and Interference for Cooperative Spectrum Sensing: A Malicious Perspective

2021

KSII TIIS

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“…The CUs having a legitimate or untrusted opinion of another node would be accepted by the entire network. Furthermore, Dubey et al [39] and Sun et al [40] proposed a trust based mechanisms in CRN based on distance and location awareness among the CUs through certain metrics such as Quality-of-Service (QoS) links and requirements. In addition, the probability based reputation mechanism was proposed to detect spectrum sensing falsification threats in the cooperative sensing approach.…”

Section: Related Workmentioning

confidence: 99%

A Trust Framework to Detect Malicious Nodes in Cognitive Radio Networks

et al. 2019

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Cognitive radio is considered as a pioneering technique in the domain of wireless communication as it enables and permits the Cognitive Users (CU) to exploit the unused channels of the Primary Users (PU) for communication and networking. The CU nodes access the vacant bands/channels through the Cognitive Radio Network (CRN) cycle by executing its different phases, which are comprised of sensing, decision making, sharing (accessing) and hand-off (mobility). Among these phases, hand-off is the most critical phase as the CU needs to switch its current data transmissions to another available channel by recalling all the previous functions upon the emergence of a PU. Further, from the security perspective, a Malicious User (MU) may imitate the PU signal with the intention to never allow the CU to use its idle band, which ultimately degrades the overall network performance. Attacks such as the Cognitive User Emulation Attack (CUEA) and Primary User Emulation Attack (PUEA) may be encountered by the handoff procedure, which need to be resolved. To address this issue, a secure and trusted routing and handoff mechanism is proposed specifically for the CRN environment, where malicious devices are identified at the lower layers, thus prohibiting them from being part of the communication network. Further, at the network layer, users need to secure their data that are transmitted through various intermediate nodes. To ensure a secure handoff and routing mechanism, a Trust Analyser (TA) is introduced between the CU nodes and network layer. The TA maintains the record of all the communicating nodes at the network layer while also computing the rating and trust value of the Handoff Cognitive User (HCUs) using the Social Impact Theory Optimizer (SITO). The simulation results suggest that the proposed solution leads to 88% efficiency in terms of better throughput of CRN during data communication, the packet loss ratio, the packet delivery ratio and the maximum and average authentication delay and clearly outperforms the prevailing mechanisms in all the parameters.

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