DocumentCode :
3542254
Title :
A novel matrix representation for privacy-preserving spatial trajectory prediction
Author :
Wen-Chen Hu ; Hung-Jen Yang ; Kaabouch, Naima ; Lei Chen
Author_Institution :
Dept. of Comput. Sci., Univ. of North Dakota, Grand Forks, ND, USA
fYear :
2013
fDate :
9-11 May 2013
Firstpage :
1
Lastpage :
7
Abstract :
Location-based services (LBS), one of mobile applications, have attracted a great attention recently. This research proposes a location-based service, which predicts a spatial trajectory based on the current and previous trajectories by using a novel matrix representation. 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 user privacy concern is a major issue. Without rigorous privacy protection, users would be reluctant to use the service. The proposed method is simple but effective and user privacy is rigorously preserved at the same time because the trajectory prediction is performed at the user-side. Additionally, this research is not only useful but also pedagogical because it involves a variety of topics like (i) mobile computing, (ii) mobile security, and (iii) human behavior recognition.
Keywords :
data privacy; matrix algebra; mobile computing; telecommunication security; LBS; human behavior recognition; location-based services; matrix representation; mobile application; mobile computing; mobile security; privacy-preserving spatial trajectory prediction; user privacy protection; Mobile communication; Privacy; Servers; Sparse matrices; Three-dimensional displays; Tiles; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electro/Information Technology (EIT), 2013 IEEE International Conference on
Conference_Location :
Rapid City, SD
ISSN :
2154-0357
Print_ISBN :
978-1-4673-5207-9
Type :
conf
DOI :
10.1109/EIT.2013.6632682
Filename :
6632682
Link To Document :
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