Ambient Backscatter: A Novel Method to Defend Jamming Attacks for Wireless Networks

Van Huynh, N; Nguyen, DN; Thai Hoang, D; Dutkiewicz, E; Mueck, M

Ambient Backscatter: A Novel Method to Defend Jamming Attacks for Wireless Networks

Van Huynh, N Nguyen, DN

Thai Hoang, D Dutkiewicz, E

Mueck, M

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Publication Type:: Journal Article
Citation:: IEEE Wireless Communications Letters, 2020, 9 (2), pp. 175 - 178
Issue Date:: 2020-02-01

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Field	Value	Language
dc.contributor.author	Van Huynh, N	en_US
dc.contributor.author	Nguyen, DN https://orcid.org/0000-0003-2659-8648	en_US
dc.contributor.author	Thai Hoang, D	en_US
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286	en_US
dc.contributor.author	Mueck, M	en_US
dc.date.issued	2020-02-01	en_US
dc.identifier.citation	IEEE Wireless Communications Letters, 2020, 9 (2), pp. 175 - 178	en_US
dc.identifier.issn	2162-2337	en_US
dc.identifier.uri	http://hdl.handle.net/10453/137805
dc.description.abstract	© 2012 IEEE. This letter introduces a novel idea to defend jamming attacks for wireless communications. In particular, when the jammer attacks the channel, the transmitter can leverage the jamming signals to transmit data by using ambient backscatter technique or harvest energy from the jamming signals to support its operation. To deal with the uncertainty of the jammer, we propose a reinforcement learning-based algorithm that allows the transmitter to obtain the optimal operation policy through real-time interaction processes with the attacker. The simulation results show the effectiveness of ambient backscatter in combating jammers, i.e., it enables the transmitter to transmit data even under the jamming attacks. We observe that the more power the jammer uses to attack the channel, the better performance the network can achieve.	en_US
dc.relation.ispartof	IEEE Wireless Communications Letters	en_US
dc.relation.isbasedon	10.1109/LWC.2019.2947417	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.title	Ambient Backscatter: A Novel Method to Defend Jamming Attacks for Wireless Networks	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	9	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	1005 Communications Technologies	en_US
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2021-11-01T00:00:00+1100
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	9	en_US

Abstract:

© 2012 IEEE. This letter introduces a novel idea to defend jamming attacks for wireless communications. In particular, when the jammer attacks the channel, the transmitter can leverage the jamming signals to transmit data by using ambient backscatter technique or harvest energy from the jamming signals to support its operation. To deal with the uncertainty of the jammer, we propose a reinforcement learning-based algorithm that allows the transmitter to obtain the optimal operation policy through real-time interaction processes with the attacker. The simulation results show the effectiveness of ambient backscatter in combating jammers, i.e., it enables the transmitter to transmit data even under the jamming attacks. We observe that the more power the jammer uses to attack the channel, the better performance the network can achieve.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/136521