Christoph Lipps

Anthony Kiggundu, Michael Zentarra, Christoph Lipps et al.

The transition to sixth-generation (6G) networks transforms wireless infrastructure into a cognitive substrate supporting Vehicle-to-Everything (V2X), Industrial IoT (IIoT), and Integrated Sensing and Communication (ISAC). In this paradigm, autonomous agentic AI performs orchestration at millisecond scales, rendering traditional static governance frameworks fundamentally inadequate for risk management. This paper introduces GIRAF(Governance-Integrated Risk and Assurance Framework), a Governance-as-Code (GaC) framework for real-time risk quantification and trust modulation in agentic 6G systems. GIRAF derives a continuous Aggregate Risk Index ($R_{t}$) from machine-readable runtime signals, including epistemic confidence, network jitter, and verification latency. A core contribution is the formalization of the verification staleness trade-off, where safety mechanisms induce risk if computational latency exceeds 6G deadlines. We demonstrate that GIRAF identifies 'Confidence Gaps' discrepancies between agent reported certainty and environmental ground truth, triggering automated safety envelopes when conditions deteriorate. Crucially, GIRAF serves as the foundational governance groundwork and conceptual 'glue' that externalizes these technical risks into machine-readable telemetry. Through simulations with fine-tuned Large Language Models (LLMs), we validate that the framework preserves operational integrity while providing the essential actuarial baseline required for multi-stakeholder liability attribution and dynamic premium quantification in the 6G ecosystem.

Seyed Nima Omidsajedi, Rekha Reddy, Jianming Yi et al.

Almost in every heavily computation-dependent application, from 6G communication systems to autonomous driving platforms, a large portion of computing should be near to the client side. Edge computing (AI at Edge) in mobile devices is one of the optimized approaches for addressing this requirement. Therefore, in this work, the possibilities and challenges of implementing a low-latency and power-optimized smart mobile system are examined. Utilizing Field Programmable Gate Array (FPGA) based solutions at the edge will lead to bandwidth-optimized designs and as a consequence can boost the computational effectiveness at a system-level deadline. Moreover, various performance aspects and implementation feasibilities of Neural Networks (NNs) on both embedded FPGA edge devices (using Xilinx Multiprocessor System on Chip (MPSoC)) and Cloud are discussed throughout this research. The main goal of this work is to demonstrate a hybrid system that uses the deep learning programmable engine developed by Xilinx Inc. as the main component of the hardware accelerator. Then based on this design, an efficient system for mobile edge computing is represented by utilizing an embedded solution.

Weinand Andreas, Andreu G. de la Fuente, Lipps Christoph et al.

Within this the work applicability of Physical LayerSecurity (PHYSEC) based key management within Long RangeWide Area Network (LoRaWAN) is proposed and evaluatedusing an experimental testbed. Since Internet of Things (IoT)technologies have been arising in past years, they have as wellattracted attention for possible cyber attacks. While LoRaWANalready provides many of the features needed in order to ensuresecurity goals such as data confidentiality and integrity, it lacksin measures such as secure key management and distributionschemes. Since conventional solutions are not feasible here, e.g.due to constraints on payload size and power consumption, wepropose the usage of PHYSEC based session key management,which can provide the respective measures in a more lightweightway. The results derived from our testbed show that it can be apromising alternative approach.

Daniel Fraunholz, Simon Duque Anton, Christoph Lipps et al.

Deception boosts security for systems and components by denial, deceit, misinformation, camouflage and obfuscation. In this work an extensive overview of the deception technology environment is presented. Taxonomies, theoretical backgrounds, psychological aspects as well as concepts, implementations, legal aspects and ethics are discussed and compared.