AllgemeinBetreuer: David Rupprecht Beginn: as soon as possible Dauer: 6 months Weitere Details:     
Long Term Evolution (LTE) is the most recent generation of mobile communication technologies and promises enhanced security features. However, recent work shows that the user's privacy can be undermined by using radio layer information to locate a victim , which imposes a serious threat to user's privacy in mobile networks. This can be accomplished by techniques such as traffic analysis, which uses encrypted or unencrypted metadata to leak sensitive information about the user behavior. Traffic analysis allows the identification of characteristic patterns even in encrypted and padded data streams, therefore an adversary is able to, e.g., distinguish between different applications just given the information leak of transmitted packets [2,3].
The student's task is to evaluate the feasibility of traffic analysis based on LTE scheduling information. For that the student should implement an analysis tool for LTE using srsLTE  or OpenAirInterface , that receives and decodes downlink as well as uplink information. Given this information, it should be analyzed how that information can be used to identify applications within a connection. Good C and C++ programming skills are required; knowledge about signal processing and Software Defined Radio (SDR) is preferable.