Mobile App Radar

Mobile apps have been a part of the everyday life of many people for quite some time now. Additionally the topic of privacy comes up in the news repeatedly, often in a negative context. [61] Yet Privacy is still something that is not easy to understand and work with, even if one is interested in the topic itself. With this thesis my goals is help every day people to make better and more informed decisions about what mobile apps they install and use. For this I will take a look at privacy in relation to mobile apps and to show based on my own findings and relevant state of the art work that privacy is an important topic. I will also introduce a prototype application called “The Mobile App Radar“ that aim to visualize the level of privacy apps have, and allows users to find alternative apps with a better level op privacy. For this I will introduce a way to compute a privacy score within the limitations of mobile devices. The same goes for a similarity score that indicates how similar two apps are. This information will then be used in combination with dimensionality reduction to create a radial visualization. This thesis is organized in chapters. Chapter 2 focuses on giving a more detailed introduction to the whole topic. Chapter 3 goes over the information that is needed to understand the context of this thesis but is not part of the direct goals I am trying to achieve. Chapter 4 introduces a whole set topics related to to Mobile App Radar and discusses them. Chapter 5 goes over the concrete implementation of the Mobile App Radar. Chapter 6 focuses on some ways to measure how good the Mobile App Radar works. At last there chapter 7, which shortly summarizes this thesis and outlines my contributions.