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The Metering Bus, also known as M-Bus, is a European standard EN13757-3 for reading out metering devices, like electricity, water, gas, or heat meters. Although real-life M-Bus networks can reach a significant size and complexity, only very simple protocol analyzers are available to observe and maintain such networks. In order to provide developers and installers with the ability to analyze the real bus signals easily, a web-based monitoring tool for the M-Bus has been designed and implemented. Combined with a physical bus interface it allows for measuring and recording the bus signals. For this at first a circuit has been developed, which transforms the voltage and current-modulated M-Bus signals to a voltage signal that can be read by a standard ADC and processed by an MCU. The bus signals and packets are displayed using a web server, which analyzes and classifies the frame fragments. As an additional feature an oscilloscope functionality is included in order to visualize the physical signal on the bus. This paper describes the development of the read-out circuit for the Wired M-Bus and the data recovery.
We provide a privacy-friendly cloud-based smart metering storage architecture which provides few-instance storage on encrypted measurements by at the same time allowing SQL queries on them. Our approach is most flexible with respect to two axes: on the one hand it allows to apply filtering rules on encrypted data with respect to various upcoming business cases; on the other hand it provides means for a storage-efficient handling of encrypted measurements by applying server-side deduplication techniques over all incoming smart meter measurements. Although the work at hand is purely dedicated to a smart metering architecture we believe our approach to have value for a broader class of IoT cloud storage solutions. Moreover, it is an example for Privacy-by-design supporting the positive-sum paradigm.
We propose secure multi-party computation techniques for the distributed computation of the average using a privacy-preserving extension of gossip algorithms. While recently there has been mainly research on the side of gossip algorithms (GA) for data aggregation itself, to the best of our knowledge, the aforementioned research line does not take into consideration the privacy of the entities involved. More concretely, it is our objective to not reveal a node's private input value to any other node in the network, while still computing the average in a fully-decentralized fashion. Not revealing in our setting means that an attacker gains only minor advantage when guessing a node's private input value. We precisely quantify an attacker's advantage when guessing - as a mean for the level of data privacy leakage of a node's contribution. Our results show that by perturbing the input values of each participating node with pseudo-random noise with appropriate statistical properties (i) only a minor and configurable leakage of private information is revealed, by at the same time (ii) providing a good average approximation at each node. Our approach can be applied to a decentralized prosumer market, in which participants act as energy consumers or producers or both, referred to as prosumers.
6LoWPAN (IPv6 over Low Power Wireless Personal Area Networks) is gaining more and more attraction for the seamless connectivity of embedded devices for the Internet of Things. It can be observed that most of the available solutions are following an open source approach, which significantly leads to a fast development of technologies and of markets. Although the currently available implementations are in a pretty good shape, all of them come with some significant drawbacks. It was therefore decided to start the development of an own implementation, which takes the advantages from the existing solutions, but tries to avoid the drawbacks. This paper discussed the reasoning behind this decision, describes the implementation and its characteristics, as well as the testing results. The given implementation is available as open-source project under [15].