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iGuard: A Personalized Privacy Guard System for Cloud Service Usage on Mobile Devices

Authors:
Chien-Wei Hu
Hewijin Jiau
Kuo-Feng Ssu

Keywords: privacy measurement; privacy protection.

Abstract:
Users encounter privacy threats when they use cloud services through mobile devices. A user leaves a large amount of usage data on the server sides. Leaving a single piece of usage data on the server side may seem harmless to user's privacy, but if usage data is all taken together, the sensitive information can be leaked. To detect privacy leakages, various privacy measurements have been proposed. However, it's not easy for the user to find suitable privacy measurements because he does not have the background knowledge. Moreover, the user also does not know what is available to be used for protecting his privacy when he finds privacy leakages. In this work, iGuard, a personalized guard system for cloud service usage on mobile devices, is provided. iGuard provides a customized privacy measurement plan which fits in the user's personal situation. The plan is executed to detect possible privacy leakages when the user is using cloud services. To resolve the leakages, iGuard also provides workable privacy protection strategies. The user can apply one of the strategies and see its effect on the privacy measurement results. According to the results, the user can tune his strategy continuously until he is satisfied with the results. By continuously tuning, the user can manage the privacy-utility trade-offs of using cloud services.

Pages: 289 to 294

Copyright: Copyright (c) IARIA, 2016

Publication date: August 21, 2016

Published in: conference

ISSN: 2308-4235

ISBN: 978-1-61208-498-5

Location: Rome, Italy

Dates: from August 21, 2016 to August 25, 2016