Two-tier Intrusion Detection Framework for Embedded Systems

Liu, M; Xue, Z; He, X

Two-tier Intrusion Detection Framework for Embedded Systems

Liu, M Xue, Z He, X

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Consumer Electronics Magazine, 2021, 10, (5), pp. 102-108
Issue Date:: 2021

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Field	Value	Language
dc.contributor.author	Liu, M
dc.contributor.author	Xue, Z
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X
dc.date.accessioned	2022-05-23T03:37:56Z
dc.date.available	2022-05-23T03:37:56Z
dc.date.issued	2021
dc.identifier.citation	IEEE Consumer Electronics Magazine, 2021, 10, (5), pp. 102-108
dc.identifier.issn	2162-2256
dc.identifier.issn	2162-2256
dc.identifier.uri	http://hdl.handle.net/10453/157626
dc.description.abstract	IEEE The embedded system is an essential component of the Internet of Everything (IoE). Recently, host-based intrusion detection techniques have been widely applied to embedded systems effectively. However, the traditional standalone intrusion detection system has several shortcomings in terms of efficiency and scalability. In this paper, a two-tier scalable intrusion detection framework is designed for embedded systems to address these shortcomings. The framework is based on Spark and is deployed in the cloud environment. The experiments show that the proposed framework can effectively reduce latency and improve the intrusion detection system's scalability.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Consumer Electronics Magazine
dc.relation.isbasedon	10.1109/MCE.2020.3048314
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Two-tier Intrusion Detection Framework for Embedded Systems
dc.type	Journal Article
utslib.citation.volume	10
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/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-05-23T03:37:55Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	10
utslib.citation.issue	5

Abstract:

IEEE The embedded system is an essential component of the Internet of Everything (IoE). Recently, host-based intrusion detection techniques have been widely applied to embedded systems effectively. However, the traditional standalone intrusion detection system has several shortcomings in terms of efficiency and scalability. In this paper, a two-tier scalable intrusion detection framework is designed for embedded systems to address these shortcomings. The framework is based on Spark and is deployed in the cloud environment. The experiments show that the proposed framework can effectively reduce latency and improve the intrusion detection system's scalability.

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

http://hdl.handle.net/10453/157626