PrivMetrics: A Framework to Secure User Privacy in Smartphones
Smartphone usage is increasing and at present most of us use smartphone. The usage of a smartphone is tightly associated with the use of third party apps as they are an essential element to experience all the features of a modern day phones. Yet how much, do we know about the apps we use. For example, do we know
1) What information the apps collect in addition to providing the intended service?
It’s common knowledge that some free apps and even paid apps are collecting personal data for various purposes and share with third-parties. Are you worried about it? If you are, is there anything you can do about? If you think about it there are not many tools helping you out here.
2) Who are the third parties receive this data?
Many third party companies such as advertising and analytics companies have access to your data thorough the apps. You might be surprised to hear that there might be over 25 companies who might be able to exact current location even if you are not connected to the internet !!.
3) Did I installed the safest app for the intended service?
When you decide to install an app for a certain function what makes you think you chose the best in the market (i.e. Reviews or Downloads which can be possible spam) ?
To address these issues we are trying to develop a framework to help the smartphone users who are concerned about privacy to make smart decisions when it comes to selecting apps.
We are developing PrivMetrics framework that enables users to make informed decisions about the use of these third party apps by providing them with an analysis on their privacy leakages and wherever possible recommending alternative apps with the same functionality as the apps they are considering which better protect their overall privacy.
Watch our video “Privmetrics”
Privmetrics app won the first prize for the best Best Mobile App contest in Mobicom 2015.
 S. Seneviratne, A. Seneviratne, D. Kaafar, A. Mahanti, P. Mohapatra. “Early Detection of Spam Mobile Apps”. To appear in Proceedings of the 24th International Conference on World Wide Web’15, Florence, Italy. May, 2015.
 S. Seneviratne, A. Seneviratne, P. Mohapatra, A. Mahanti. “Predicting user traits from a snapshot of apps installed on a smartphone”. In Proceedings of the ACM SIGMOBILE Computing and Communications Review Volume 18 Issue 2 p1-8.
 S Seneviratne, A Seneviratne, P Mohapatra, A Mahanti. “Your installed apps reveal your gender and more!”. In Proceedings of the ACM SIGMOBILE Computing and Communications Review Volume 18 Issue 3 p55-61.
 S. Seneviratne, A. Seneviratne, J. Kestenare. “PrivMetrics: A Framework for Quantifying User Privacy in Smartphones”. W3C Workshop on Privacy and User Centric Controls, Berlin, Germany, November 2014.
 S. Seneviratne, J. Kestenare, A. Seneviratne, D. Kaffar, P. Mohapatra ”PrivMetrics: Quantifying User Privacy in Smartphones” [Highlycommended Poster Award in the 2014 ADC PhD School in Big Data. Brisbane, Australia, Jul 2014].