Characterization of privacy based on context sensitivity and user preference for multimedia context-aware on IoT
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In an IoT environment, building a Context-Aware system is mandatory and can provide a suitable and timely (just-in-time) service suited to the context of the user. In addition, the IoT environment is made on the assumption that maximum collection of the user’s context is done. However, if the context of the user is collected beyond necessary, or when a context the user did not agree with was collected, a problem arises regarding a violation on the user’s privacy. Asking for the user’s approval on the collection of all context brings unnecessarily many steps and inconvenience to the users. Therefore, there is a need for user preferences to be dynamically controlled by the system. An IoT system must adjust its preferences so that it provides the maximum context to the service provider and minimizes the intrusion of the user’s privacy. However, the current Context-Aware IoT does not consider these problems. Therefore, there is a need for a Dynamic Preference structure that protects the privacy of the user. This paper uses quantitative methods in formalizing the Privacy Invasion Value (PIV) of the users and discusses the methods in minimizing the PIV values through Dynamic Preference. The method used in this paper can solve privacy infringement issues in the Context-Aware IoT environment.
KeywordsMultimedia-awareness, context-aware Privacy protection Context sensitivity User preference PIV (privacy invasion value) IoT (internet of things)
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2016R1D1A1B03931689). This work was also supported by the Dongguk University Research Fund of 2017.
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