Modeling Privacy Preservation in Smart Connected Toys by Petri-Nets

dc.contributor.author Yankson, Benjamin
dc.contributor.author Iqbal, Farkhund
dc.contributor.author Lu, Zhihui
dc.contributor.author Wang, Xiaoling
dc.contributor.author Hung, Patrick
dc.date.accessioned 2019-01-02T23:55:56Z
dc.date.available 2019-01-02T23:55:56Z
dc.date.issued 2019-01-08
dc.description.abstract Children data privacy must be considered as integral and factored into the system design of Smart Connected Toy (SCT). The challenge is that SCTs are capable to gather significant amount volunteered and non-volunteered data, which lacks privacy considerations. It is imperative to adopt a modeling technique that autonomously preserves privacy and secure children’s data in SCT transactions. This paper surveys the current data flow modeling techniques, which most of them do not have elements to address the privacy of Personal Identifiable Information (PII). This paper shows a Petri-Net simulation which provides privacy assurance in order to minimize the risk of privacy violation of a child’s PII and related data.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2019.207
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59610
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Machine Learning, Robotic, and Toy Computing
dc.subject Decision Analytics, Mobile Services, and Service Science
dc.subject Smart Connected Toys (SCT), Petri-Nets, Privacy, Data Flow Modeling, Simulation
dc.title Modeling Privacy Preservation in Smart Connected Toys by Petri-Nets
dc.type Conference Paper
dc.type.dcmi Text
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