@inproceedings{ubicomp2011,
 abstract = {A promising approach to location privacy is query obfuscation, which involves reporting k -- 1 false locations along with the real location. In this paper, we examine the level of privacy protection provided by the current query obfuscation techniques against adversarial location service providers. As a representative and realistic implementation of query obfuscation, we focus on SybilQuery. We present two types of attacks depending upon whether or not a short-term query history is available. When history is available, using machine learning, we were able to identify 93.67% of user trips, with only 2.02% of fake trips misclassified, for the security parameter k = 5. In the absence of history, we used trip correlations to form a smaller set of trips effectively increasing the user query identification probability from 20% to about 40%. Our work demonstrates that the use of aggregate statistical information alone is not sufficient to generate simulated trips. We identify areas for improvement in the existing query obfuscation techniques.},
 address = {New York, NY, USA},
 author = {Peddinti, Sai Teja and Saxena, Nitesh},
 booktitle = {Proceedings of the 13th International Conference on Ubiquitous Computing},
 doi = {10.1145/2030112.2030139},
 isbn = {9781450306300},
 keywords = {anonymity, location privacy, machine learning, query obfuscation},
 location = {Beijing, China},
 numpages = {10},
 pages = {187-196},
 publisher = {Association for Computing Machinery},
 series = {UbiComp '11},
 title = {On the limitations of query obfuscation techniques for location privacy},
 url = {https://doi.org/10.1145/2030112.2030139},
 year = {2011}
}