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Please use this identifier to cite or link to this item: http://10.10.120.238:8080/xmlui/handle/123456789/188
Title: Smart Data Agent for Preserving Location Privacy
Authors: Kaur H.
Echizen I.
Kumar R.
Keywords: Deep Learning
Internet of Things
Location Privacy
Neural Networks
Privacy by Design
Smart Data
Issue Date: 2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: A novel agent model is proposed that preserves the privacy of location information by using smart data i.e., data that protect themselves in a manner appropriate to the needs of the user. The model protects personal data by wrapping in a 'cloak of intelligence'. This requires development of an intelligent agent that acts as the user's virtual proxy in cyberspace controlling the release of the user's information in accordance with the its preferences, context of information and/or nature of situation. The presented work focuses on developing a location data agent for smartphone users. Many applications request access to the user's location data in order to provide their services, but some may take advantage of this opportunity to continuously record location data even when they are not being used. This continuous tracking of the user's location can reveal extensive personal information. The aim of this work is to develop a neural network based intelligent agent that learns the user's privacy preferences and estimates the preferred privacy levels for future interactions. Agent in the proposed model behaves as an advanced data location manager and interacts with the apps instead of letting them directly access the location data. Apart from deciding the amount of distortion, the agent also works to prevent remove spatial and temporal correlations by adding perturbations to actual access history so as to prevent a third party from making an kind of prediction on personal data. © 2020 IEEE.
URI: https://dx.doi.org/10.1109/SSCI47803.2020.9308396
http://localhost:8080/xmlui/handle/123456789/188
ISBN: 978-1728125473
Appears in Collections:Conference Paper

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