5G Secure Communications in Industrial Production Environments
Security enhancements through localization in Wireless Sensor Networks
Thesis advisor: Andreas Springer
Doctoral student: Nuria Ballber Torres
Security in Wireless Sensor Networks (WSN), especially for industrial environments, has been a greatly studied topic in recent years. Traditionally, it has been based mainly on cryptographic methods because of its robustness. However, in certain settings cryptographic methods can be crashed or are not available. In this thesis, we study how node localization methods based on propagation time measurements in WSNs can be used together with cryptographic methods to prevent attacks and enhance security in real world scenarios. Our work is focused on secure authentication schemes that combine localization with traditional cryptographic methods, such as distance bounding, that can be improved when adding time-based node location methods.
CSI-based Localization for Secure IoT systems
Thesis advisor: Andreas Springer
Doctoral student: Eshagh Dehmollaian
Cybersecurity for Internet-of-Things (IoT) applications is gaining increasing attention. Among many types of available data in IoT systems, accurate node location information can be an important factor for security. In this thesis, we will research node localization methods for OFDM-based wireless networks. Using the channel state information of the wireless links, signal processing algorithms for pattern matching will be applied for localization. The estimated locations of the nodes should be used to enhance the security of wireless networks by combating distance fraud attacks.