This paper describes the functionality and realisation of the smart metering infrastructure in the Netherlands, and discusses the changes that have been made in plans in response to privacy and security concerns. We also discuss the rationale for introducing smart meters-which is less clear than one would expect or indeed hope-and ongoing developments in the use of smart metering information in local energy community pilots.

There has been a huge increase in interest in blockchain technology. However, little is known about the drivers behind the adoption of this technology. In this article we identify and analyze these drivers, using six real-world and representative scenarios. We confirm in our analysis that blockchain is not an appropriate technology for some scenarios, from a purely technical point of view. The choice for blockchain technology in such scenarios may therefore seem as an irrational choice. However, our analysis reveals that there are nontechnical drivers at play that drive the adoption of blockchain, such as philosophical beliefs, network effects, and economic incentives. These nontechnical drivers may explain the rationality behind the choice for blockchain adoption.

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Industrial Control Systems are under increased scrutiny. Their security is historically sub-par, and although measures are being taken by the manufacturers to remedy this, the large installed base of legacy systems cannot easily be updated with state-of-the-art security measures. We propose a system that uses electromagnetic side-channel measurements to detect behavioural changes of the software running on industrial control systems. To demonstrate the feasibility of this method, we show it is possible to profile and distinguish between even small changes in programs on Siemens S7-317 PLCs, using methods from cryptographic side-channel analysis.

Abstract. Physically unclonable functions (PUFs) provide data that can be used for cryptographic purposes: on the one hand randomness for the initialization of random-number generators; on the other hand individual fingerprints for unique identification of specific hardware components. However, today's off-the-shelf personal computers advertise randomness and individual fingerprints only in the form of additional or dedicated hardware. This paper introduces a new set of tools to investigate whether intrinsic PUFs can be found in PC components that are not advertised as containing PUFs. In particular, this paper investigates AMD64 CPU registers as potential PUF sources in the operating-system kernel, the bootloader, and the system BIOS; investigates the CPU cache in the early boot stages; and investigates shared memory on Nvidia GPUs. This investigation found non-random non-fingerprinting behavior in several components but revealed usable PUFs in Nvidia GPUs.