Anomaly detection of user behaviour in smartphones

Anomaly detection of user behaviour in smartphones

Master Thesis

Motivation
Mobile phones have become essential devices that people carry around everywhere they go. These devices contain important personal and confidential information, such as pictures, emails and login credentials, which make them a prime for theft. A user with the knowledge that their device has been stolen is able to prevent further damage with tools that remotely contact the device. These technologies are useless, however, if the user does not know that the device has been stolen or if a remote connection is not possible.
In this project we are going to create technologies that are capable of automatically detecting when a mobile phone has been stolen without human intervention. These technologies will learn the behavior of the owner and will recognize when the device is no longer being used by the owner. Once it is discovered that there is someone else using the device, it will lock itself up and try to contact back the owner.

The realization of this technology will be in the form of an Android application lock the mobile device up in such a way that only the owner of the device will be able to unlock it. We will use artificial intelligence to learn and distinguish between different user behaviors.

Start: 19.12.2014

Ende: 19.06.2015

Betreuer:

  • Carlos Garcia C. (carlos.garcia(a-t)tk.informatik.tu-darmstadt.de)

Forschungsgebiete: CASED, Telecooperation , – SSI – Area Secure Smart Infrastructures