The energy sector is part of the critical infrastructure in modern society where security and privacy concerns of the customers of this infrastructure have been well studied and addressed. In the classical power grid, consumers are being supplied by a major power grid operator who has been government-sanctioned and therefore has to adhere to privacy and security guidelines. In recent years, however, with the shift to the usage of renewable energies, new concepts for the trading of energy flexibilities have emerged, that enable consumers with their own energy production to sell their spare energy back to the market. While reducing the load from the grid operators by enabling peer-to-peer trading between grid participants, this comes with new privacy concerns, which have to be addressed and regulated.This work proposes a conceptual framework based on Self-Sovereign Identity (SSI) to establish a secure and private peer-to-peer trading system between energy market participants, which provides the participants control over their own digital identity and what data these participants want to share with peers. Furthermore, this work discusses the proposal’s effects and implications on system security and user privacy.

The deployment of 5G technology has the potential to usher in a new era for the internet of things (IoT). The introduction of new use cases, such as massive machine-type communications (mMTC), referring to a large number of IoT devices, resulting in the increasing importance of 5G as the basic communication infrastructure for IoT. However, the increasing connectivity of IoT devices coincides with a number of risks to security. Many IoT sensors have limited resources and, therefore, cannot perform the complex security measures required to protect them from attacks and data loss. Furthermore, IoT networks are very scattered, distributed and dynamic, so decentralised security measures are required. To address these challenges, this poster proposes the integration of attribute-based access control (ABAC) into the 5G service-based architecture. This approach aims to prevent unauthorized access to IoT devices at the network level, thereby alleviating the computational burden on resource-constrained IoT devices. By implementing ABAC, the proposed solution offers a more efficient method for managing access control within the IoT landscape in the context of 5G networks.

Indoor positioning is a challenging topic - especially for sensor nodes in spatial areas or buildings. By now only few publications are available for LoRaWAN-based localisation due to different challenges such as a poor signal-noise-ratio or hierarchical system architectures. The following paper presents a multi-step-approach with a dynamic optimal algorithm selection for LoRaWAN networks with a modified stack for direct peer communication. With slightly increased computational effort on the peers, a deviation of below 5m could be achieve d without extensive offline environmental surveying. We examine several filtering and compensation, and selection algorithms to minimize the influence of measurement errors. However, the primary advantage of the method is the small number of anchor nodes required due to the high range of the transmitters. The LoRa transmitters’ overall low acquisition and maintenance costs make the approach interesting for applications in large rooms where the accuracy of about ten meters is sufficient. We demonstrate this potential with a series of conducted experiments.