A complete algorithm to diagnose and alleviate the effects of physical layer attacks

Sasa Maric; Audri Biswas; Sam Reisenfeld

doi:10.1109/ICSIGSYS.2017.7967058

A complete algorithm to diagnose and alleviate the effects of physical layer attacks

Sasa Maric, Audri Biswas, Sam Reisenfeld

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

3 Citations (Scopus)

Abstract

In this paper we present a method to diagnose and mitigate against primary user emulation attacks (PUEA) in cognitive radio networks. We develop a hybrid algorithm that uses a combination of compressed sensing and belief propagation to identify and combat PUEAs. We propose to use compressive sensing in the fusion centre to localise a primary user, the distribute the primary user location to secondary users in order to establish theoretical data for comparison and then use a variant of belief propagation at each secondary user to diagnose primary user emulation attacks. Using a central-distributed hybrid approach ensure that our algorithm is highly adaptable, accurate and simple to implement.

Original language	English
Title of host publication	International Conference on Signals and Systems (ICSigSys) 2017 : proceedings
Place of Publication	Piscataway, NJ, USA
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	29-34
Number of pages	6
ISBN (Electronic)	9781509067480
ISBN (Print)	9781509067497
DOIs	https://doi.org/10.1109/ICSIGSYS.2017.7967058
Publication status	Published - 30 Jun 2017
Event	1st IEEE International Conference on Signals and Systems, ICSigSys 2017 - Bali, Indonesia Duration: 16 May 2017 → 18 May 2017

Other

Other	1st IEEE International Conference on Signals and Systems, ICSigSys 2017
Country/Territory	Indonesia
City	Bali
Period	16/05/17 → 18/05/17

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10.1109/ICSIGSYS.2017.7967058

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title = "A complete algorithm to diagnose and alleviate the effects of physical layer attacks",

abstract = "In this paper we present a method to diagnose and mitigate against primary user emulation attacks (PUEA) in cognitive radio networks. We develop a hybrid algorithm that uses a combination of compressed sensing and belief propagation to identify and combat PUEAs. We propose to use compressive sensing in the fusion centre to localise a primary user, the distribute the primary user location to secondary users in order to establish theoretical data for comparison and then use a variant of belief propagation at each secondary user to diagnose primary user emulation attacks. Using a central-distributed hybrid approach ensure that our algorithm is highly adaptable, accurate and simple to implement.",

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Maric, S, Biswas, A & Reisenfeld, S 2017, A complete algorithm to diagnose and alleviate the effects of physical layer attacks. in International Conference on Signals and Systems (ICSigSys) 2017 : proceedings., 7967058, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, USA, pp. 29-34, 1st IEEE International Conference on Signals and Systems, ICSigSys 2017, Bali, Indonesia, 16/05/17. https://doi.org/10.1109/ICSIGSYS.2017.7967058

A complete algorithm to diagnose and alleviate the effects of physical layer attacks. / Maric, Sasa; Biswas, Audri; Reisenfeld, Sam.
International Conference on Signals and Systems (ICSigSys) 2017 : proceedings. Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 29-34 7967058.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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N2 - In this paper we present a method to diagnose and mitigate against primary user emulation attacks (PUEA) in cognitive radio networks. We develop a hybrid algorithm that uses a combination of compressed sensing and belief propagation to identify and combat PUEAs. We propose to use compressive sensing in the fusion centre to localise a primary user, the distribute the primary user location to secondary users in order to establish theoretical data for comparison and then use a variant of belief propagation at each secondary user to diagnose primary user emulation attacks. Using a central-distributed hybrid approach ensure that our algorithm is highly adaptable, accurate and simple to implement.

AB - In this paper we present a method to diagnose and mitigate against primary user emulation attacks (PUEA) in cognitive radio networks. We develop a hybrid algorithm that uses a combination of compressed sensing and belief propagation to identify and combat PUEAs. We propose to use compressive sensing in the fusion centre to localise a primary user, the distribute the primary user location to secondary users in order to establish theoretical data for comparison and then use a variant of belief propagation at each secondary user to diagnose primary user emulation attacks. Using a central-distributed hybrid approach ensure that our algorithm is highly adaptable, accurate and simple to implement.

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Y2 - 16 May 2017 through 18 May 2017

ER -

A complete algorithm to diagnose and alleviate the effects of physical layer attacks

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