Securing data transmission in Internet of Things

Zha, Xuan

Securing data transmission in Internet of Things

Zha, Xuan

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Publication Type:: Thesis
Issue Date:: 2019

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Field	Value	Language
dc.contributor.author	Zha, Xuan
dc.date.accessioned	2019-12-02T03:28:34Z
dc.date.available	2019-12-02T03:28:34Z
dc.date.issued	2019
dc.identifier.uri	http://hdl.handle.net/10453/137105
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_AU
dc.description.abstract	The Internet of Things (IoT) is poised to transform our lives and unleash enormous economic benefit. With the rise in the number of connected IoT devices, the potential vulnerabilities in IoT increase as well. The IoT security faces severe challenges arising from its specific characteristics. This thesis studies the location privacy protection and secure data transmission issues in IoT to ensure the data confidentiality, integrity, non-repudiation and availability. Markov models are proposed to analyse the network performance of secure data transmission mechanisms, providing quantified criteria for selecting appropriate secure transmission protocols in various network environments. The main contributions of this thesis are as follows, (1) An anti-pollution source-location privacy scheme is proposed to tackle the conflict between the source-location protection and authentications. The proposed protocol consists of key predistribution mechanisms and a homomorphic signature algorithm, for filtering out polluted and dummy packets at intermediate nodes while concealing the packet trajectory. The proposed protocol improves the message delivery rate and saves energy as compared with previous works. (2) A probabilistic encrypted data transmission protocol is proposed to transmit messages in confidentiality in an adaptive manner. It avoids the communication overhead caused by handshaking in previous data encryption protocols. In addition, a three-dimensional (3D) Markov model is constructed to analyse the impact of wireless communication collisions and key predistributions on the performance of encrypted data transmissions. The analysis and simulation results prove the accuracy of the 3D Markov model. (3) An authentication protocol is proposed in opportunistic routing based IoT networks. In order to improve the authentication efficiency, the proposed protocol generates authentication information based on the combination of the new message and previous non-conflict but unauthenticated messages while attempting different keys. A new 3D Markov model is designed to accurately capture the interaction process among non-coordinated transmissions, key selections and packet lifetime. The proposed protocol substantially improves the tolerance against changing topologies and resistance against collusion attacks, as compared to the prior art. (4) A four-dimensional (4D) Markov model is designed to analyse the impact of dynamic topology on opportunistic authentication protocols. Three cross-layer data authentication protocols are proposed with opportunistic authentication and channel access coupled to different extent. According to the simulation results, the 4D model is general and accurate. The analysis results prove that opportunistic data authentication protocols significantly improve the authentication rate, reduce authentication delay and enhance scalability to dense mobile distributed networks.	en_AU
dc.format	Thesis (PhD)
dc.language.iso	en_AU	en_AU
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/137105/2/02whole.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	au.edu.uts.lib/ppc
dc.subject	secure data transmission
dc.subject	secure transmission
dc.subject	internet of things
dc.subject	internet privacy
dc.subject	privacy protection
dc.subject	data protection
dc.subject	data security
dc.subject	Markov model
dc.subject	security testing
dc.subject	encrypted data
dc.subject	authentication protocol
dc.subject	opportunistic routing
dc.title	Securing data transmission in Internet of Things	en_AU
dc.type	Thesis	en_AU
utslib.copyright.status	open_access

Abstract:

The Internet of Things (IoT) is poised to transform our lives and unleash enormous economic benefit. With the rise in the number of connected IoT devices, the potential vulnerabilities in IoT increase as well. The IoT security faces severe challenges arising from its specific characteristics. This thesis studies the location privacy protection and secure data transmission issues in IoT to ensure the data confidentiality, integrity, non-repudiation and availability. Markov models are proposed to analyse the network performance of secure data transmission mechanisms, providing quantified criteria for selecting appropriate secure transmission protocols in various network environments. The main contributions of this thesis are as follows, (1) An anti-pollution source-location privacy scheme is proposed to tackle the conflict between the source-location protection and authentications. The proposed protocol consists of key predistribution mechanisms and a homomorphic signature algorithm, for filtering out polluted and dummy packets at intermediate nodes while concealing the packet trajectory. The proposed protocol improves the message delivery rate and saves energy as compared with previous works. (2) A probabilistic encrypted data transmission protocol is proposed to transmit messages in confidentiality in an adaptive manner. It avoids the communication overhead caused by handshaking in previous data encryption protocols. In addition, a three-dimensional (3D) Markov model is constructed to analyse the impact of wireless communication collisions and key predistributions on the performance of encrypted data transmissions. The analysis and simulation results prove the accuracy of the 3D Markov model. (3) An authentication protocol is proposed in opportunistic routing based IoT networks. In order to improve the authentication efficiency, the proposed protocol generates authentication information based on the combination of the new message and previous non-conflict but unauthenticated messages while attempting different keys. A new 3D Markov model is designed to accurately capture the interaction process among non-coordinated transmissions, key selections and packet lifetime. The proposed protocol substantially improves the tolerance against changing topologies and resistance against collusion attacks, as compared to the prior art. (4) A four-dimensional (4D) Markov model is designed to analyse the impact of dynamic topology on opportunistic authentication protocols. Three cross-layer data authentication protocols are proposed with opportunistic authentication and channel access coupled to different extent. According to the simulation results, the 4D model is general and accurate. The analysis results prove that opportunistic data authentication protocols significantly improve the authentication rate, reduce authentication delay and enhance scalability to dense mobile distributed networks.

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