Abstract
The popularity of mobile devices, especially intelligent mobile phones, significantly prompt various location-based services (LBSs) in cloud systems. These services not only greatly facilitate people’s daily lives, but also cause serious threats that users’ location information may be misused or leaked by service providers. The dummy-based privacy protection techniques have significant advantages over others because they neither rely on trusted servers nor need adequate number of trustworthy peers. Existing dummy-based location privacy protection schemes, however, cannot yet provide long-term privacy protection. In this paper, we propose four principles for the dummy-based long-term location privacy protection (LT-LPP). Based on the principles, we propose a set of long-term consistent dummy generation algorithms for the LT-LPP. Our approach is built on soft computing techniques and can balance the preferred privacy protection and computing cost. Comprehensive experimental results demonstrate that our approach is effective to both long-term privacy protection and fake path generation for LBSs in mobile clouds.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China (NSFC) projects (Nos. 91438121 and 61373156), the Key Basic Research Project (No. 12JC1405400) of the Shanghai Municipality, the Shanghai Pujiang Program (No. 13PJ1404600) the National Basic Research Program of China (No. 2015CB352400), and Shanghai Branch of Southwest Electron and Telecom Technology Research Institute Project (No. 2013008).
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Communicated by A. Jara, M. R. Ogiela, I. You and F.-Y. Leu.
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Tang, F., Li, J., You, I. et al. Long-term location privacy protection for location-based services in mobile cloud computing. Soft Comput 20, 1735–1747 (2016). https://doi.org/10.1007/s00500-015-1703-8
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DOI: https://doi.org/10.1007/s00500-015-1703-8