Challenges and New Directions in Securing Spectrum Access Systems

Shi, Shanghao; Xiao, Yang; Lou, Wenjing; Wang, Chonggang; Li, Xu; Hou, Y. Thomas; Reed, Jeffrey H.

doi:10.1109/jiot.2021.3064583

Cited by 17 publications

(11 citation statements)

References 82 publications

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“…Weaknesses in communication protocols [18] can be exploited to intercept or alter data flow between RL agents and their environments, compromising the decision-making process. The dependence on wireless communications exposes RL systems to spectrum-based attacks [30,43,41,42], such as jamming or spoofing [29], potentially crippling their functionality. Moreover, the involvement of untrusted or compromised service providers magnifies the threat landscape, facilitating malicious activities like data tampering or unauthorized data access [45,7,6].…”

Section: Adversarial Examples Attack and Defensementioning

confidence: 99%

Cyberspace attack and defense game based on reward randomization reinforcement learning

Zhang

Pan

et al. 2022

Array

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Section: Adversarial Examples Attack and Defensementioning

confidence: 99%

Cyberspace attack and defense game based on reward randomization reinforcement learning

Zhang

Pan

et al. 2022

Array

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“…Javaid et al introduced signal correlation factors into the traditional energy detection threshold [25]. In [26], Shi et al analyzed the spectrum access systems to ensure their security and privacy against attacks. The spectrum sharing strategy in satellite systems was proposed by Wang et al [27].…”

Section: Relevant Workmentioning

confidence: 99%

Intelligent Spectrum Sensing Algorithm for Cognitive Internet of Vehicles Based on KPCA and Improved CNN

Duan

Gulliver³

2022

Preprint

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With the acceleration of economic globalization and integration, the global trade is becoming more frequent, which promotes the vigorous development of transportation industry. In recent years, the Internet of Vehicle (IoV) has developed rapidly in the transportation industry, and the number of IoV users has exploded. The requirements for IoV communication services are very high, resulting in the lack of spectrum resources. Rather than utilizing traditional spectrum resource allocation methods, cognitive radio technology makes full use of idle frequency bands, improving the IoV communication spectrum’s utilization rate. Spectrum sensing is the primary link to realize a cognitive radio. However, IoV mobile communication environment is characterized by complexity, dynamism, and substantial noise interference, thus imposing significant challenges to spectrum sensing. Thus, this paper proposes an intelligent spectrum sensing algorithm based on kernel principal component analysis (KPCA) and an improved convolutional neural network (CNN). Since the wireless signal cannot distinguish the signal and noise linearly, KPCA maps the sampled signal to a high-dimensional space, creates a covariance matrix, and obtains eigenvector data of the signal and noise through matrix decomposition. A spectrum sensing classifier based on improved CNN is proposed, and the dynamic threshold is obtained via offline training. Compared with the traditional algorithm, the designed deep CNN improves the model’s training speed, enables parameter sharing, and reduces the number of model parameters, effectively reducing the computational complexity. Additionally, due to the extracted signal feature’s small dimension, the algorithm reduces the number of pooling layers and avoids the effective features’ loss, thus increasing the detection probability. Finally, the proposed algorithm achieves a 10% higher sensing accuracy than support vector machine (SVM), Elman, and LeNet5 algorithms, signaling its robustness.

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“…Smart contract, one of the most popular DApps, realizes complex multiparty business logic and sees wide adoption in novel business scenarios, such as decentralized finance, digital identity, and supply chain management. The decentralized and zero-trust nature, consensus-based security, transparency, and irreversible ledger make blockchain a promising technology for enabling various dynamic spectrum sharing scenarios for 5G and beyond, as is envisioned in recent surveys [8], [9]. And crucially, blockchain smart contract provides an automated computing platform for realizing spectrum access assignment (e.g., calculating an assignment based on a request and an interference model) and enforcing spectrum regulations.…”

Section: Prospect Of Blockchain Solutions To Decentralized Sasmentioning

confidence: 99%

“…One major challenge lies in the "securitization" of spectrum access rights and the enforcement of trades, since wireless spectrum, unlike ordinary financial or physical assets, is selfexistent and intangible. Another challenge remains in realizing the business model of a blockchain-based spectrum exchange, including trader incentives, orders matching, commission fee assessment [8], [9]. To address these challenges, we expect a multidisciplinary approach involving blockchain, finance, and wireless communications.…”

Section: Broader Challenges and Opportunitiesmentioning

confidence: 99%

Decentralized Spectrum Access System: Vision, Challenges, and a Blockchain Solution

Xiao,

Shi,

Lou

et al. 2021

Preprint

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Spectrum access system (SAS) is widely considered the de facto solution to coordinating dynamic spectrum sharing (DSS) and protecting incumbent users. The current SAS paradigm prescribed by the FCC for the CBRS band and standardized by the WInnForum follows a centralized service model in that a spectrum user subscribes to a SAS server for spectrum allocation service. This model, however, neither tolerates SAS server failures (crash or Byzantine) nor resists dishonest SAS administrators, leading to serious concerns on SAS system reliability and trustworthiness. This is especially concerning for the evolving DSS landscape where an increasing number of SAS service providers and heterogeneous user requirements are coming up. To address these challenges, we propose a novel blockchain-based decentralized SAS architecture called BD-SAS that provides SAS services securely and efficiently, without relying on the trust of each individual SAS server for the overall system trustworthiness. In BD-SAS, a global blockchain (G-Chain) is used for spectrum regulatory compliance while smart contract-enabled local blockchains (L-Chains) are instantiated in individual spectrum zones for automating spectrum access assignment per user request. We hope our vision of a decentralized SAS, the BD-SAS architecture, and discussion on future challenges can open up a new direction towards reliable spectrum management in a decentralized manner.

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Challenges and New Directions in Securing Spectrum Access Systems

Cited by 17 publications

References 82 publications

Cyberspace attack and defense game based on reward randomization reinforcement learning

Cyberspace attack and defense game based on reward randomization reinforcement learning

Intelligent Spectrum Sensing Algorithm for Cognitive Internet of Vehicles Based on KPCA and Improved CNN

Decentralized Spectrum Access System: Vision, Challenges, and a Blockchain Solution

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