Veto: Prohibit Outdated Edge System Software from Booting - Röckl, Jonas; Wagenhäuser, Adam; Müller, Tilo (In Proceedings of the 9th International Conference on Information Systems Security and Privacy (ICISSP), 2023)
Edge computing emerges as a trend, forming a link between the Internet of Things and cloud-based services. Large-scale edge deployments are already in place today in the context of communication network providers that offload more and more tasks to the edge to ensure high flexibility and low latencies. By relying on remote attestation and disk encryption techniques, we design a novel system architecture that protects confidential data on edge nodes in the case of device theft. Recent vulnerabilities like Ripple20 and Amnesia:33 show the consequences and costs of critical security bugs stemming from outdated system software. Thus, we design our system in a way that a node can derive its decryption key if and only if a trusted remote party (e.g., a network operator) can verify that it is running the latest software. This is a security feature that prevalent implementations like Linux’s dm-crypt lack. To secure the early-boot communication, we rely on a trusted execution environment, hardware offloading, and Rust device drivers. We prototype our system on two recent ARMv8 devices and show that the performance overhead (≈ 2%) and the boot delay (1s) are low. Thus, we believe that our concept is a meaningful step towards more secure future edge devices. <br
Keywords: Trusted Execution Environment; Full Disk Encryption; Remote Attestation; Edge Computing.

What does Power Consumption Behavior of HPC Jobs Reveal?: Demystifying, Quantifying, and Predicting Power Consumption Characteristics - Patel, Tirthak; Wagenhäuser, Adam; Eibel, Christopher; Hönig, Timo; Zeiser, Thomas; Tiwari, Devesh (Proceedings - 2020 IEEE 34th International Parallel and Distributed Processing Symposium, IPDPS 2020, 2020)
As we approach exascale computing, large-scale HPC systems are becoming increasingly power-constrained, requiring them to run HPC workloads in an energy-efficient manner. The first step toward achieving this goal is to better understand, analyze, and quantify the power consumption characteristics of HPC jobs. However, there is a lack of understanding of the power consumption characteristics of HPC jobs which run on production HPC systems. Such characterization is required to guide the design of the next generation of power-aware resource management. To the best of our knowledge, we are the first study to open-source the data and analysis of power-consumption characteristics of HPC jobs and users from two medium-scale production HPC clusters.
Created from Fastlane, Scopus look-up