TY - JOUR
T1 - A context-aware scheme for privacy-preserving location-based services
AU - Pingley, Aniket
AU - Yu, Wei
AU - Zhang, Nan
AU - Fu, Xinwen
AU - Zhao, Wei
N1 - Funding Information:
This work was supported in part by the National Science Foundation under Grants 1117297 , 0915834 , 0852673 , 0852674 , 1116644 , 0942113 , 0958477 and 0943479 and 1117175 . Any opinions, findings, conclusions, and/or recommendations expressed in this material, either expressed or implied, are those of the authors and do not necessarily reflect the views of the sponsor listed above.
PY - 2012/7/31
Y1 - 2012/7/31
N2 - We address issues related to privacy protection in location-based services (LBSs). Most existing privacy-preserving LBS techniques either require a trusted third-party (anonymizer) or use cryptographic protocols that are computationally and communicationally expensive. Our design of privacy-preserving techniques is principled on not requiring a trusted third-party while being highly efficient in terms of time and space complexities. The problem has two interesting and challenging characteristics: First, the degree of privacy protection and LBS accuracy depends on the context, such as population and road density, around a user's location. Second, an adversary may violate a user's location privacy in two ways: (i) based on the user's location information contained in the LBS query payload and (ii) by inferring a user's geographical location based on the device's IP address. To address these challenges, we introduce CAP, a context-aware privacy-preserving LBS system with integrated protection for both data privacy and communication anonymity. We have implemented CAP and integrated it with Google Maps, a popular LBS system. Theoretical analysis and experimental results validate CAP's effectiveness on privacy protection, LBS accuracy, and communication QoS (Quality-of-Service).
AB - We address issues related to privacy protection in location-based services (LBSs). Most existing privacy-preserving LBS techniques either require a trusted third-party (anonymizer) or use cryptographic protocols that are computationally and communicationally expensive. Our design of privacy-preserving techniques is principled on not requiring a trusted third-party while being highly efficient in terms of time and space complexities. The problem has two interesting and challenging characteristics: First, the degree of privacy protection and LBS accuracy depends on the context, such as population and road density, around a user's location. Second, an adversary may violate a user's location privacy in two ways: (i) based on the user's location information contained in the LBS query payload and (ii) by inferring a user's geographical location based on the device's IP address. To address these challenges, we introduce CAP, a context-aware privacy-preserving LBS system with integrated protection for both data privacy and communication anonymity. We have implemented CAP and integrated it with Google Maps, a popular LBS system. Theoretical analysis and experimental results validate CAP's effectiveness on privacy protection, LBS accuracy, and communication QoS (Quality-of-Service).
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U2 - 10.1016/j.comnet.2012.03.022
DO - 10.1016/j.comnet.2012.03.022
M3 - Article
AN - SCOPUS:84863331774
SN - 1389-1286
VL - 56
SP - 2551
EP - 2568
JO - Computer Networks
JF - Computer Networks
IS - 11
ER -