Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/59610

Modeling Privacy Preservation in Smart Connected Toys by Petri-Nets

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Title:Modeling Privacy Preservation in Smart Connected Toys by Petri-Nets
Authors:Yankson, Benjamin
Iqbal, Farkhund
Lu, Zhihui
Wang, Xiaoling
Hung, Patrick
Keywords:Machine Learning, Robotic, and Toy Computing
Decision Analytics, Mobile Services, and Service Science
Smart Connected Toys (SCT), Petri-Nets, Privacy, Data Flow Modeling, Simulation
Date Issued:08 Jan 2019
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.
Pages/Duration:10 pages
URI/DOI:http://hdl.handle.net/10125/59610
ISBN:978-0-9981331-2-6
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Machine Learning, Robotic, and Toy Computing


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