Optimizing Privacy in the Personal Cloud

OData support
Imre Gábor
Department of Automation and Applied Informatics

Cloud storage provides an easy-to-use way of storing personal information on servers that are available on the Internet. This allows us to access our data regardless of the place, time and device we use. However, when our files are shared in the currently available cloud services, a lot of additional information is shared alongside them that we are unaware of. This is called metadata. A few examples of metadata are: author, creation date, GPS coordinates etc. The goal of this project was to allow automatic assessment of the files’ privacy risk levels and provide that assessment to users along with recommendations on how to minimize the privacy risk through privacy enhancing technologies. To tackle this issue a Java based system was developed that puts more control into the user’s hands. It allows setting exactly what is shared regarding both content and metadata. Furthermore, the application offers different sharing and content hiding mechanisms dependent on the file type. These mechanisms include allowing the user to share only a brief summary of a document or a just a thumbnail of a picture at a given resolution etc. The software’s goal was not to develop a new cloud service solution but to provide an additional layer above the already existing ones. The scope of the thesis is the design and development of the client application, but the full solution includes a server side service that calculates the risk of sharing the file, based on aggregated, crowdsourced information and context analysis.


Please sign in to download the files of this thesis.