Near-Rand: Noise-based Location Obfuscation Based on Random Neighboring Points

In recent years Location-Based Information Systems have increased its popularity in the market of mobile applications, however, due to the ability of smartphones and similar devices to estimate location in real time using GPS or through network providers; it is critical to implement techniques to protect such sensitive information while still make it available to the service provider. This paper presents Near-Rand, a new random noise-based location obfuscation technique. This algorithm generates random points around the real location of the user within a neighbor-size squared area and calculates the n nearest points average to the user's location giving as result an obfuscated point. Compared to Pinwheel, another noise-based obfuscation mechanism, it shows a similar performance against Exponentially Moving Average-based filtering attacks, while being able to use non-uniformly distributions for random points.