Mobile privacy risk refers to the privacy risk that occurs when personal data is collected by other parties in the use of mobile devices. We mainly focus on the potential privacy risk of Android system, a free and open-sourced operating system. Since Android platform allows users to install all kinds of APP files downloaded from various applicaition markets and websites. When people use some APPs, personal data may be obtained by applicaiton developers and other third-parties. How to measure personal privacy risk at this time and put forward corresponding privacy protection methods are the main problem we study.
With the rapid development of mobile systems and application markets, users are faced with huge personal privacy risks while enjoying the services provided by various APPs. At present, privacy group of WAMDM lab mainly focuses on privacy risk quantification and active privacy preserving, then propose a quantificatioin model of personal privacy risk on mobile platform. Based on this, we have designed and implement an App privacy risk accessment system, AppPrivacy, which can simulate user's operations with some apps, monitor user behaviors, quantify personal privacy risk and provide early warning.
- S. Guo, X. Meng. Density Peaks Clustering with Differential Privacy[C]. Proceedings of the 8th Biennial Conference on Innovative Data Systems Research(CIDR),2017, Chaminade, CA.
- X. Zhang, C. Shao, X. Meng. Accurate Histpgram Release under Differential Privacy[J].Journal of Computer Research and Development, Vol 53 (05):1106-1117,2016.
- L. Wang, X. Meng, S. Guo.Preservation of Implicit Privacy in Spatio-Temporal Data Publication[J].Journal of Software, Vol 27(08):1922-1933,2016.
- X. Zhang, X. Meng.Streaming Histogram Publication Method with Differential Privacy. Journal of Software, Vol 27(02):381-393,2016.
- L. Wang, R. Ma, X. Meng: Evaluating k Nearest Neighbor Query on Road Networks with no Information Leakage[C]. Proceedings of the 16th International Conference on Web Information Systems Engineering (WISE), pages:508-521, 2015, Miami, Florida.
- L.Wang, X.Meng, Hu H, et al. Bichromatic Reverse Nearest Neighbor Query Without Information Leakage[C]. Proceedings of the20th International Conferenceon Database Systems for Advanced Applications (DASFAA),pages:609-624,2015,Hanoi, Vietnam.
- X. Meng, X. Zhang. Big Data Privacy Management[J]. Journal of Computer Research and Development,2015,02:265-281.[PDF]
- X. Zhang, R. Chen, J. Xu, X. Meng. Towards Accurate Histogram Publication under Differential Privacy. Accepted for publication in Proceedings of the 14th SIAM International Conference on Data Mining (SDM 2014): 587-595, Philadelphia, Pennsylvania, USA. (Full Paper)
- X. Zhang, X. Meng. Discovering top-k patterns with differential privacy-an accurate approach. Frontiers of Computer Science. Vol 8(5): 816-827, 2014.
- X. Zhang, X. Meng: Differential Privacy in Data Publication and Analysis. Chinese Journal of Computers. Vol 37(4):927-949, 2014, 4.
- X. Zhang, M. Wang, X. Meng: An Accurate Method for Mining top-k Frequent Pattern under Differential Privacy. Journal of Computer Research and Development. Vol 51(1): 104-114, 2014, 1.
- L. Wang, X. Meng: Location Privacy Preservation in Big Data Era: A Survey. Journal of Software. Vol 25(4): 693-712, 2014.
- X. Zhang, X. Meng, R. Chen: Differential Private Set-Valued Data Release against Incremental Updates. In Proceedings of the 18th International Conference on Database Systems for Advanced Applications (DASFAA 2013): 392-406. April 22-25, 2013, Wuhan, China. (Regular paper)
- X. Pan, X. Meng: Preserving location privacy without exact locations in mobile services. Frontiers of Computer Science Vol.7(3): 317-340 , 2013.
- Z. Huo, X. Meng, R. Zhang: Feel Free to Check In: Privacy Alert against Hidden Location Inference Attacks in GeoSN. In Processings of the 18th International Conference on Database Systems for Advanced Applications (DASFAA 2013): 377-491. April 22-25, 2013, Wuhan, China. (Regular paper)
- Z. Huo, X. Meng, H. Hu, Y. Huang: You Can Walk Alone: Trajectory Privacy-Preserving through Significant Stays Protection. In Proceedings of the 17th International Conference of Database Systems for Advanced Applications (DASFAA 2012), pages: 351-366, April 15-19, 2012, Busan, South Korea.
- X. Pan, J. Xu, X. Meng: Protecting Location Privacy Against Location-dependent Attacks in Mobile Services. IEEE Transaction on Knowledge and Data Engineering (TKDE).24(8):1506-1519,2012 .(Regular paper)
- Z. Huo, Y. Huang, X. Meng: History Trajectory Privacy-preserving through Graph Partition. In Proceedings of the 1st International Workshop on Mobile Location-Based Service (MLBS 2011, in conjunction with Ubicomp). September 17-21, Beijing, 2011: 71-78 .
- Z. Huo, X. Meng: A Survey of Trajectory Privacy-Preserving Techniques. Chinese Journal of Computers, Vol 34(10):1820-1830, 2011,10.
- X. Pan, X. Hao, X. Meng: Privacy Preserving Towards Continuous Query in Location-Based Services. Journal of Computer Research and Development, Vol.47(1): 121-129, 2010.1.
- X. Pan, X. Meng, J. Xu: Distortion-based Anonymity for Continuous Query in Location-Based Mobile Services. In Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2009):256-265, November 4-6, 2009, Seattle, Washington. (FULL paper)
- X. Min, H. Wang, J. Yin, X. Meng: Providing Freshness Guarantees for Outsourced Databases. In Proceedings of the 11th International Conference on Extending Database Technology(EDBT2008), page 323-332, Nantes, France, March 25-30, 2008. ( Full paper)
- X. Min, H. Wang, J. Yin, X. Meng: Integrity Auditing of Outsourced Data. In Proceedings of the 33th International Conference on Very Large Data Bases(VLDB2007), pages 782-793, Vienner, Austria, September 24-28, 2007.
- PScout. http://pscout.csl.toronto.edu/
- Harvard University Privacy Tools Project. https://privacytools.seas.harvard.edu/differential-privacy
- PrivMetrics. http://www.privmetrics.org/
- PINQ. https://www.microsoft.com/en-us/research/project/privacy-integrated-queries-pinq/?from=http%3A%2F%2Fresearch.microsoft.com%2Fen-us%2Fprojects%2Fpinq%2Ftutorial.aspx
- Airavat. http://z.cs.utexas.edu/users/osa/airavat/
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