DocumentCode :
137519
Title :
Privacy-Preserving Spatial Trajectory Prediction
Author :
Wen-Chen Hu ; Kaabouch, Naima ; Mousavinezhad, S. Hossein ; Hung-Jen Yang
Author_Institution :
Dept. of Comput. Sci., Univ. of North Dakota Grand Forks, Grand Forks, ND, USA
fYear :
2014
fDate :
15-16 May 2014
Firstpage :
69
Lastpage :
73
Abstract :
One of the location-based services, spatial trajectory prediction, can be used in a variety of purposes such as travel recommendations and traffic control and planning, but at the same time, just like most location-based services, the concern of user privacy is a major issue. Without rigorous privacy protection, users would be reluctant to use the services. This research proposes a privacy-preserving method of predicting a spatial trajectory based on the current and previous trajectories by using a matrix representation. Preliminary experimental results show this method is effective and secure for spatial trajectory prediction.
Keywords :
data privacy; information services; matrix algebra; location-based services; matrix representation; privacy protection; privacy-preserving spatial trajectory prediction; traffic control; traffic planning; travel recommendation; user privacy; Educational institutions; Mobile radio mobility management; Privacy; Servers; Three-dimensional displays; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Research Collaboration Symposium (NWRCS), 2014 National
Conference_Location :
Idaho Falls, ID
Type :
conf
DOI :
10.1109/NWRCS.2014.17
Filename :
6942506
Link To Document :
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