Detecting Primary User Emulation Attacks in Cognitive Radio Networks via Physical Layer Network Coding

Xie, Xiongwei; Wang, Weichao

doi:10.1016/j.procs.2013.09.057

Cited by 36 publications

(17 citation statements)

References 14 publications

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“…In a PUE attack, a malicious node attains the PU characteristics; thus, causing the CR nodes to perceive the malicious node as a PU [230], [231]. The malicious node may force the CR node to vacate the occupied channel or the malicious node may jam the CR user's spectrum sensing process.…”

Section: Referencementioning

confidence: 99%

Cognitive Radio for Smart Grids: Survey of Architectures, Spectrum Sensing Mechanisms, and Networking Protocols

Khan

Rehmani

Reisslein

2016

IEEE Commun. Surv. Tutorials

312

145

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Traditional power grids are currently being transformed into Smart Grids (SGs). SGs feature multi-way communication among energy generation, transmission, distribution, and usage facilities. The reliable, efficient, and intelligent management of complex power systems requires integration of highspeed, reliable, and secure data information and communication technology into the SGs to monitor and regulate power generation and usage. Despite several challenges, such as trade-offs between wireless coverage and capacity as well as limited spectral resources in SGs, wireless communication is a promising SG communications technology. Cognitive Radio Networks (CRNs) in particular are highly promising for providing timely SG wireless communications by utilizing all available spectrum resources. We provide in this paper a comprehensive survey on the CRN communication paradigm in SGs, including the system architecture, communication network compositions, applications, and CR-based communication technologies. We highlight potential applications of CR-based SG systems. We survey CR-based spectrum sensing approaches with their major classifications. We also provide a survey on CR-based routing and MAC protocols, and describe interference mitigation schemes. We furthermore present open issues and research challenges faced by CR-based SG networks along with future directions.Index Terms-Advanced metering infrastructure (AMI), Communication architecture, Cognitive radio network (CRN), Smart grid (SG).1553-877X (c) 2 to license holders on a long-term basis for large geographical regions. This fixed spectrum allocation can result in inefficient spectrum utilization. Cognitive radios (CRs) operating on the principle of Dynamic Spectrum Access (DSA) may be a suitable option to solve these spectrum inefficiency problems [18]. CRs use the existing spectrum through opportunistic access to the licensed bands without interfering with the licensed users. CRs determine the spectrum portions unoccupied by the licensed users known as spectrum holes or white spaces, and allocate the best available channels for CR communication [19], [20].After identification of available spectrum holes, the spectrum utilization can be improved through joint spatial and temporal spectrum sharing. SG applications, especially demand response management, can benefit from joint spatial and temporal spectrum sharing [21]. Machine-to-machine (M2M) communication is an emerging paradigm for providing ubiquitous connectivity between devices to communicate autonomously without human intervention. However, a high number of connected devices can heavily congest the spectrum in existing communication networks. CR technology may be a suitable option for mitigating the potential spectrum shortage arising from M2M communications in the SG [22]. B. Contribution of this Survey ArticleWhile a few overview articles have outline some selected aspects of CR communication in the SG [23]- [25], to the best of our knowledge, there is no prior survey that comprehensively covers CR-based...

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Section: Referencementioning

confidence: 99%

Cognitive Radio for Smart Grids: Survey of Architectures, Spectrum Sensing Mechanisms, and Networking Protocols

Khan

Rehmani

Reisslein

2016

IEEE Commun. Surv. Tutorials

312

145

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“…In [13], Jin et al argue that location-based solutions like the ones proposed in [11,12,14] usually require a dedicated wireless sensor network to assist the localization of transmitters. Thus, they design a different scheme that employ the received signal strength as decision criterion.…”

Section: Related Workmentioning

confidence: 99%

A framework for resilient and secure spectrum sensing on cognitive radio networks

Soto

Nogueira

2015

Computer Networks

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“…There are two types of malicious attacks in CSS [7,8]. The first one is the incumbent emulation attack (IEA), where some malicious users know the characteristics of the primary signal and transmit a signal with similar characteristics so that other secondary users would believe that a primary user is present [9][10][11]. The second one is the spectrum sensing data falsification attack (SSDF) also termed as Byzantine attack, where malicious users send false sensing information intentionally to a central node [12,13].…”

Section: Introductionmentioning

confidence: 99%

Efficient elimination of erroneous nodes in cooperative sensing for cognitive radio networks

Srinu

Mishra

2016

Computers & Electrical Engineering

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Detecting Primary User Emulation Attacks in Cognitive Radio Networks via Physical Layer Network Coding

Cited by 36 publications

References 14 publications

Cognitive Radio for Smart Grids: Survey of Architectures, Spectrum Sensing Mechanisms, and Networking Protocols

Cognitive Radio for Smart Grids: Survey of Architectures, Spectrum Sensing Mechanisms, and Networking Protocols

A framework for resilient and secure spectrum sensing on cognitive radio networks

Efficient elimination of erroneous nodes in cooperative sensing for cognitive radio networks

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