A Survey on Byzantine Attack using Secure Cooperative Spectrum Sensing in Cognitive Radio Sensor Network

Patil, Siddarama R.; Rajashree, Rajashree; Agarkhed, Jayashree

doi:10.1109/iccmc53470.2022.9753781

Cited by 5 publications

(2 citation statements)

References 24 publications

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“…In SSDF attack, malicious IoT devices intentionally report false local sensing results to the FC and then mislead it into making an incorrect global decision, thereby selfishly occupying the spectrum resources or causing harmful interference to the normal communication of the PU. 3 Recently proposed large-scale SSDF poses a unique and significant threat to CSS with defense mechanisms. To be specific, large-scale SSDF attack can lead to significant performance degradation of CIoTs and even result in network failures, that is, the FC will lose the ability to make final decisions and get the wrong result of reputation value under large-scale attack, because of the blind problem.…”

Section: Introductionmentioning

confidence: 99%

“…However, the openness of the CSS framework also makes it susceptible to various attacks, such as spectrum sensing data falsification (SSDF) attack. In SSDF attack, malicious IoT devices intentionally report false local sensing results to the FC and then mislead it into making an incorrect global decision, thereby selfishly occupying the spectrum resources or causing harmful interference to the normal communication of the PU 3 . Recently proposed large‐scale SSDF poses a unique and significant threat to CSS with defense mechanisms.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic sliding window‐cooperative spectrum sensing against massive SSDF attack in interweave cognitive internet of things

Zhu,

Wu,

et al. 2024

Trans Emerging Tel Tech

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To improve spectrum utilization, cognitive radio (CR) enables unauthorized internet of thing (IoT) devices to opportunistically access the channel underutilized by the primary user (PU) in a cognitive IoT (CIoT). To this end, cooperative spectrum sensing (CSS) plays a crucial role in CR technology, which leverages the spatial diversity of corroborative IoT devices to accurately detect the PU signal. However, this open cooperative paradigm may suffer from spectrum sensing data falsification (SSDF) attack in which malicious IoT devices intentionally mislead the fusion center (FC) by providing false sensing results to make an incorrect global decision regarding the PU status. To effectively characterize the attack behavior of malicious IoT devices, we propose a massive SSDF attack model described by the attack cycle and malicious ratio within a sensing period to characterize the malicious behaviors. Additionally, we introduce a delivery evaluation mechanism and propose a dynamic sliding window‐CSS (DSW‐CSS) to mitigate the impact of massive SSDF attack. Moreover, we introduce a sequential reporting mechanism to further reduce the number of samples required by the global decision‐making of the FC. Finally, simulation results show the flexibility and aggressiveness of the proposed attack model and demonstrate the correctness and effectiveness of DSW‐CSS.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%