Paper Info
Title
A Real-Time Data Collection Mechanism With Trajectory Privacy in Mobile Crowd-Sensing
Abstract
As a new paradigm to serve and sense the intelligent city, mobile crowd-sensing (MCS) usually requires participants’ real-time locations. However, uploading participants’ true locations to servers or third parties raises privacy concerns. In this letter, we propose a real-time data collection mechanism with trajectory privacy (RDCTP) in MCS, which achieves <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$w$ </tex-math></inline-formula> -event <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -differential privacy for the crowd-sensing participants. Different from existing works, we focus on protecting the privacy of trajectories instead of individual locations. Specifically, RDCTP provides <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -differential privacy for each sub-trajectory which consists of successive <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$w$ </tex-math></inline-formula> locations. To achieve this, a participant first allocates the trajectory privacy budget to each location. Then, he perturbs his true location and gets candidate location set which satisfies <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -differential privacy. Last, he submits a location from the set by solving an optimization problem that aims to tradeoff between the privacy and utility. We utilize real world traffic trajectories of Shanghai taxis to evaluate the RDCTP, and the results show that it not only protects participants’ privacy, but also preserves the server’s utility.
Year
DOI
Venue
2020
10.1109/LCOMM.2020.3003997
IEEE Communications Letters
Keywords
DocType
Volume
Privacy,Trajectory,Servers,Differential privacy,Real-time systems,Data collection
Journal
24
Issue
ISSN
Citations 
10
1089-7798
2
PageRank 
References 
Authors
0.37
0
3
Name
Order
Citations
PageRank
Xin Niu15611.39
Hongyu Huang227721.83
Yantao Li3164.65