For many years, there has been a race between web trackers trying to find techniques to monitor users behaviour online and privacy researchers looking for solutions to avoid such tracking. Despite many progresses in browsers privacy preserving techniques, IP tracking remains very effective because current solutions to hide an IP address such as VPNs or the Tor network rely on external services and often induce a high cost in terms of performance.

We proposed an approach based on short-lived random identifiers to allow applications to detect and opportunistically use networks where multiple users share the same IP address such as Carrier-grade NATs. Using these networks allows to evade some of the tracking as the traffic of all users is merged into a single IP flow. User traffic is then harder to single out. We developed an Android application using this method in order to obtain measurements on the feasibility and potential gains of the technique.

This application generates random identifiers and periodically sends them to a reporting server. The server stores the identifiers and the IP addresses used to send them in order to study if IP tracking mechanism can uniquely identify a given user. All information you provide will be treated anonymously and confidentially. Neither your name nor your contact details will be collected, stored nor made public. We will also keep confidential all the IP addresses and the identifiers gathered during the measurements. Only dummy values will be used to illustrate approaches, theories or model. If you have any question regarding the application or the data collected, feel free to contact us at.