With the ongoing adoption of remotely communicating and interacting control systems harbored by critical infrastructures, the potential attack surface of such systems also increases drastically. Therefore, not only the need for standardized and manufacturer-agnostic control system communication protocols has grown, but also the requirement to protect those control systems’ communication. There have already been numerous security analyses of different control system communication protocols; yet, these have not been combined with each other sufficiently, mainly due to three reasons: First, the life cycles of such protocols are usually much longer than those of other Internet and communication technologies, therefore legacy protocols are often not considered in current security analyses. Second, the usage of certain control system communication protocols is usually restricted to a particular infrastructure domain, which leads to an isolated view on them. Third, with the accelerating pace at which both control system communication protocols and threats against them develop, existing surveys are aging at an increased rate, making their re-investigation a necessity. In this paper, a comprehensive survey on the security of the most important control system communication protocols, namely Modbus, OPC UA, TASE.2, DNP3, IEC 60870-5-101, IEC 60870-5-104, and IEC 61850 is performed. To achieve comparability, a common test methodology based on attacks exploiting well-known control system protocol vulnerabilities is created for all protocols. In addition, the effectiveness of the related security standard IEC 62351 is analyzed by a pre-and post-IEC 62351 comparison.

Until recently, there have been relatively few studies exploring the power consumption of ICT resources in data centres. In this paper, we propose a methodology to capture the behaviour of most relevant energy-related ICT resources in data centres and present a generic model for them. This is achieved by decomposing the design process into four modelling phases. Furthermore, unlike the state-of-the-art approaches, we provide detailed power consumption models at server and storage levels. We evaluate our model for different types of servers and show that it suffers from an error rate of 2% in the best case, and less than 10% in the worst case.

Quantum algorithms often use quantum random access memory (QRAM) for accessing information stored in a databaselike manner. QRAM has to be fast, resource efficient, and fault tolerant. The latter is often influenced by access speeds, because shorter times introduce less exposure of the stored information to noise. The total execution time of an algorithm depends on the QRAM access time which includes (i) address translation time and (ii) effective query time. The bucket-brigade QRAM was proposed to achieve faster addressing at the cost of exponentially many ancillas. We illustrate a systematic method to significantly reduce the effective query time by using $\mathrm{Clifford}+T$ gate parallelism. The method does not introduce any ancilla qubits. Our parallelization method is compatible with the surface code quantum error correction. We show that parallelization is a result of advantageous Toffoli gate decomposition in terms of $\mathrm{Clifford}+T$ gates, and after addresses have been translated, we achieve theoretical $O\left(1\right)$ parallelism for the effective queries. We conclude that, in theory, (i) fault-tolerant bucket-brigade quantum RAM queries can be performed approximately with the speed of classical RAM, and (ii) the exponentially many ancillas from the bucket-brigade addressing scheme are a tradeoff cost for achieving exponential query speedup compared to quantum read-only memories whose queries are sequential by design. The methods used to compile, parallelize, and analyze the presented QRAM circuits have been implemented in software which is available online.

The power demand (kW) and energy consumption (kWh) of data centers were augmented drastically due to the increased communication and computation needs of IT services. Leveraging demand and energy management within data centers is a necessity. Thanks to the automated ICT infrastructure empowered by the IoT technology, such types of management are becoming more feasible than ever. In this paper, we look at management from two different perspectives: (1) minimization of the overall energy consumption and (2) reduction of peak power demand during demand-response periods. Both perspectives have a positive impact on total cost of ownership for data centers. We exhaustively reviewed the potential mechanisms in data centers that provided flexibilities together with flexible contracts such as green service level and supply-demand agreements. We extended state-of-the-art by introducing the methodological building blocks and foundations of management systems for the above mentioned two perspectives. We validated our results by conducting experiments on a lab-grade scale cloud computing data center at the premises of HPE in Milano. The obtained results support the theoretical model, by highlighting the excellent potential of flexible service level agreements in Green IT: 33% of overall energy savings and 50% of power demand reduction during demand-response periods in the case of data center federation.

The future of e-mobility will consist of a large number of connected electric vehicles, smart charging stations and information systems at the intersection of electricity and mobility sector. When engineering and integrating the multitude of systems into even more complex systems-of-systems for e-mobility, interoperability and complexity handling are vital. Model-based system architectures support the engineering process of information systems with the concepts of abstraction, reduction and separation of concerns. In this paper, we contribute to the research body, by extracting requirements for managing complexity and interoperability of these systems. Further, a comparative analysis of the state-of-the-art in existing architecture models and frameworks for e-mobility is conducted. Based on the identified gaps in existing research, we propose the E-Mobility Systems Architecture (EMSA) Model, a three-dimensional systems architecture model for the e-mobility sector. Its structure originates from the well-established Smart Grid Architecture Model. We further allocate all relevant entities from the e-mobility sector to the EMSA dimensions, including a harmonized role model, functional reference architecture, component and systems allocation, as well as a mapping of data standards and communication protocols. The model then is validated qualitatively and quantitatively against the requirements with a case study approach. Our evaluation shows that the EMSA Model fulfills all requirements regarding the management of complexity and ensuring interoperability. From the case study, we further identify gaps in current data model standardization for e-mobility.