E3S Web Conf.
Volume 184, 20202nd International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED 2020)
|Number of page(s)||6|
|Published online||19 August 2020|
Smart Privacy Protection for Location-Based Services using Queueing Modelling
1 Student, Department of CSE, GRIET, Hyderabad, India
2 Student, Department of CSE, GRIET, Hyderabad, India
3 Associate Professor, Department of CSE, GRIET, Hyderabad, India
4 Associate Professor, Department of Humanities and Basic Sciences, GRIET, Hyderabad, India
* Corresponding author: firstname.lastname@example.org
In the digital era, we are greatly dependent on the popular applications of the Location Based Services (LBS) in our day-to-day activities. The smart phone comes with a variety of applications which acquire the user location and build up user profile like the user activities, hobbies, places of visit, food orders etc. Such sensitive information in the LBS server can pose privacy risk for the user. To safe guard the user from such threat we propose a smart privacy protection technique in this paper that can conceal the user location when using the location based services. We adopt the generation of dummy locations to obfuscate the user original location from the LBS server. The server generates the result set for the dummy user locations. In this work we try to optimize the things at server as well as user ends with two objectives. The first goal is to work towards identifying the overlap in result sets and generate unique and reduced result set with which the communication load on the network can be reduced. The second goal is to prioritize the result set by Queuing model for the result set through which waiting time of the customer can be minimized. We have also illustrated that this model show good performance in terms of the reduced communication load through experimental results.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.