Publication:
Fault tree analysis-based risk quantification of smart homes

dc.contributor.authorChanoksuda Wongvisesen_US
dc.contributor.authorAssadarat Khuraten_US
dc.contributor.authorDoudou Fallen_US
dc.contributor.authorShigeru Kashiharaen_US
dc.contributor.otherNara Institute of Science and Technologyen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2019-08-23T10:57:59Z
dc.date.available2019-08-23T10:57:59Z
dc.date.issued2018-01-12en_US
dc.description.abstract© 2017 IEEE. A smart home is a new enabling innovative appliance domain that is developed from the rapid growth of the Internet of Things. Despite its popularity and evident usefulness for human beings, smart homes have numerous security issues that originate from the heterogeneous, wide-scale and complex structure of the Internet of Things. It is obvious that a risk assessment is needed in order to ensure the security of smart homes. We propose a security risk quantification technique that permits to have a measure of the level of security of a given smart home based on the 'things' that it is composed of. Our method is based on Fault Tree Analysis which is the de-facto tool used in mission-critical systems. At first, we generated an exhaustive security tree based on the general architecture of a smart home. Afterwards, we evaluated our proposal in a use case of successful attacks on a light bulb system that functions through the ZigBee protocol. We were able to demonstrate that the risk of a successful attack in that system is very high given the same conditions.en_US
dc.identifier.citationProceeding of 2017 2nd International Conference on Information Technology, INCIT 2017. Vol.2018-January, (2018), 1-6en_US
dc.identifier.doi10.1109/INCIT.2017.8257865en_US
dc.identifier.other2-s2.0-85049449031en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/123456789/45656
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85049449031&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.titleFault tree analysis-based risk quantification of smart homesen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85049449031&origin=inwarden_US

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