Joint Spectrum Sensing and Spectrum Access for Defending Massive SSDF Attacks: A Novel Defense Framework

Xu, Zhenyu; Sun, Zhiguo; Guo, Lili; Muhammad, Zahid Hammad; Tellambura, Chintha

doi:10.1049/cje.2021.00.090

Cited by 9 publications

(3 citation statements)

References 40 publications

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“…In addition, Miao et al 12 proposed a spectrum sensing strategy to employ weighted combining of the hidden Markov model. In References 13–15, the authors tried to defend large‐scale attacks with the help of trusted SU. However, due to the complex and unpredictable nature of a real sensing environment, the assumption about the performance of trusted SU/node is unrealistic.…”

Section: Motivation and Contributionmentioning

confidence: 99%

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: Motivation and Contributionmentioning

confidence: 99%

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

View full text Add to dashboard Cite

show abstract

“…To gain further insight, we discuss the diversity order of PR1, PR2 and SR. According to [7], the diversity order is defined as…”

Section: ) Outage Probability For Sr X Smentioning

confidence: 99%

“…However, it also faces great challenges, such as spectrum shortage and large-scale connections [6]. In order to effectively solve the above problems, some promising technologies have been proposed, such as non-orthogonal multiple access (NOMA) [7] and cognitive radio [8].…”

Section: Introductionmentioning

confidence: 99%

Overlay CR-NOMA Assisted Intelligent Transportation System Networks with Imperfect SIC and CEEs

Xingwang,

Xuesong,

Yingting

et al. 2023

Chinese J. Elect.

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With the development of the mobile communication and intelligent information technologies, the intelligent transportation systems driven by the sixth generation (6G) has many opportunities to achieve ultralow latency and higher data transmission rate. Nonetheless, it also faces the great challenges of spectral resource shortage and large-scale connection. To solve the above problems, non-orthogonal multiple access (NOMA) and cognitive radio (CR) technologies have been proposed. In this regard, we study the reliable and ergodic performance of CR-NOMA assisted intelligent transportation system networks in the presence of imperfect successive interference cancellation (SIC) and non-ideal channel state information. Specifically, the analytical expressions of the outage probability (OP) and ergodic sum rate (ESR) are derived through a string of calculations. In order to gain more insights, the asymptotic expressions for OP and ESR at high signal-to-noise ratio (SNR) regimes are discussed. We verify the accuracy of the analysis by Monte Carlo simulations, and the results show: i) Imperfect SIC and channel estimation errors (CEEs) have negative impacts on the OP and ESR; ii) The OP decreases with the SNR increasing until convergence to a fixed constant at high SNR regions; iii) The ESR increases with increasing SNR and there exists a ceiling in the high SNR region.

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An Optimized Security Sensing Method Based on Pignistic Evidence Distance

Yang

2023

Lecture Notes in Electrical Engineering

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Joint Spectrum Sensing and Spectrum Access for Defending Massive SSDF Attacks: A Novel Defense Framework

Cited by 9 publications

References 40 publications

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

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

Overlay CR-NOMA Assisted Intelligent Transportation System Networks with Imperfect SIC and CEEs

An Optimized Security Sensing Method Based on Pignistic Evidence Distance

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