A Roadmap to Smart Homes Security Aided SDN and ML

Altaf, T; Braun, R

A Roadmap to Smart Homes Security Aided SDN and ML

Altaf, T Braun, R

Permalink

Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2022 5th Conference on Cloud and Internet of Things (CIoT), 2022, 00, pp. 129-136
Issue Date:: 2022-01-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (670.17 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Altaf, T
dc.contributor.author	Braun, R https://orcid.org/0000-0002-4153-8769
dc.date	2022-03-28
dc.date.accessioned	2023-01-16T04:31:29Z
dc.date.available	2023-01-16T04:31:29Z
dc.date.issued	2022-01-01
dc.identifier.citation	2022 5th Conference on Cloud and Internet of Things (CIoT), 2022, 00, pp. 129-136
dc.identifier.isbn	9781665479646
dc.identifier.uri	http://hdl.handle.net/10453/165008
dc.description.abstract	The smart home is one of those significant technology trends which enhances comfort and allows the integration of environment-friendly smart applications in daily life. It contains a large pool of internet-enabled devices some of which have a limited capability and operate in a specific manner. Due to heterogeneity and operational complexity, home networks pose extremely challenging vulnerabilities concerning privacy and security. This paper is a review of recent attempts to provide privacy and security in IoT smart homes. We summarize the research efforts in the past few years, discuss and classify them based on technologies deployed i.e. SDN, ML. We then propose an approach for the integration of SDN with ML in the home network for an automatic and reconfigurable network security mechanism. We emphasize that the proposed approach addresses the heterogeneity and scalability issues (by implementing SDN) as well as pave ways to prevent harmful attacks efficiently and in a timely manner.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2022 5th Conference on Cloud and Internet of Things (CIoT)
dc.relation.ispartof	2022 5th Conference on Cloud and Internet of Things (CIoT)
dc.relation.isbasedon	10.1109/ciot53061.2022.9766525
dc.rights	info:eu-repo/semantics/openAccess
dc.title	A Roadmap to Smart Homes Security Aided SDN and ML
dc.type	Conference Proceeding
utslib.citation.volume	00
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	open_access	*
dc.date.updated	2023-01-16T04:31:25Z
pubs.finish-date	2022-03-30
pubs.publication-status	Published
pubs.start-date	2022-03-28
pubs.volume	00

Abstract:

The smart home is one of those significant technology trends which enhances comfort and allows the integration of environment-friendly smart applications in daily life. It contains a large pool of internet-enabled devices some of which have a limited capability and operate in a specific manner. Due to heterogeneity and operational complexity, home networks pose extremely challenging vulnerabilities concerning privacy and security. This paper is a review of recent attempts to provide privacy and security in IoT smart homes. We summarize the research efforts in the past few years, discuss and classify them based on technologies deployed i.e. SDN, ML. We then propose an approach for the integration of SDN with ML in the home network for an automatic and reconfigurable network security mechanism. We emphasize that the proposed approach addresses the heterogeneity and scalability issues (by implementing SDN) as well as pave ways to prevent harmful attacks efficiently and in a timely manner.

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

http://hdl.handle.net/10453/165008