geopriv4j

KO | EN

gitlite — search

#python #typescript #go #android #machine-learning #rust #docker #nodejs #kubernetes #vue #pytorch #security #mcp #open-source

(★ 9)

Geopriv4j: An Open Source Repository for Practical Location Privacy

geopriv4j Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Geopriv4j: An Open Source Repository for Location Privacy
Geopriv4j implements location privacy methods in Java (JDK 14.0.1).  Methods in the repository do not rely on other trusted parties/users/servers, and protect the user's location on-the-fly.  Please see the below for a list of methods currently implemented in the repository.

## Location Privacy Methods:

### Generalization-based:
* Rounding/trucation - This method has been implemented from the paper by Krumm, John. "Inference attacks on location tracks." International Conference on Pervasive Computing. Springer, Berlin, Heidelberg, 2007 [paper](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/12/inference-attack-refined02-distribute.pdf) and  Micinski, Kristopher, Philip Phelps, and Jeffrey S. Foster. "An empirical study of location truncation on android." Weather 2 (2013): 21. [paper](http://www.cs.tufts.edu/~jfoster/papers/most13.pdf)
* Spatial cloaking - This method has been implemented from the paper by Krumm, John. "Inference attacks on location tracks." International Conference on Pervasive Computing. Springer, Berlin, Heidelberg, 2007. [paper](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/12/inference-attack-refined02-distribute.pdf)

### Dummy-based:
* SpotME - This has been implemented based on the paper by D. Quercia, I. Leontiadis, L. McNamara, C. Mascolo and J. Crowcroft, "SpotME If You Can: Randomized Responses for Location Obfuscation on Mobile Phones," 2011 31st International Conference onDistributed Computing Systems, Minneapolis, MN, 2011, pp. 363-372. [paper](https://ieeexplore.ieee.org/document/5961717)
* Moving in the Neighborhood - This method is implemented based on the paper by H. Kido, Y. Yanagisawa and T. Satoh, "An anonymous communication technique using dummies for location-based services," ICPS '05. Proceedings. International Conference on Pervasive Services, 2005., Santorini, Greece, 2005, pp. 88-97. [paper](https://ieeexplore.ieee.org/abstract/document/1506394)

### Perturbation-based:
* Noise - This method has been implemented from the paper by Krumm, John. "Inference attacks on location tracks." International Conference on Pervasive Computing. Springer, Berlin, Heidelberg, 2007. [paper](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/12/inference-attack-refined02-distribute.pdf)
* Various-sized Hilbert Curve - This has been implemented based on the paper by Pingley, Aniket, et al. "Cap: A context-aware privacy protection system for location-based services." 2009 29th IEEE International Conference on Distributed Computing Systems. IEEE, 2009. [paper](https://www2.seas.gwu.edu/~nzhang10/cap/cap/Welcome_files/paper.pdf)
* Laplace - This method is implemented based on the paper by Andrés, Miguel E., et al.  "Geo-indistinguishability: Differential privacy for location-based systems." Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security. 2013. [paper](http://www.lix.polytechnique.fr/~catuscia/papers/Geolocation/geo.pdf)

*Installation Note:* You must provide your own gurobi.jar file either in your build path or by placing it in geopriv4j/lib/. The gurobi.jar file can be found in your Gurobi installation folder.

## Usage Examples
A usage example is provided for each location privacy method.  Synthetic location traces can be found in "data".

## Test Android App
A sample app is provided to illustrate the adoption of location privacy methods.  [Video](https://drive.google.com/file/d/1IBTvD7EH-sFyUZmwia_x1HBBpUMpulZO/view?usp=sharing)

See [testApp](https://github.com/fan-group/geopriv4j/tree/master/testApp) for more details.

*Acknolwedgement:* This research has been supported in part by NSF grant CNS-1951430 and UNC Charlotte. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the sponsors.

geopriv4j

geopriv4j Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

geopriv4j

geopriv4j Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README