Fakultät Informatik und Mathematik
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A Wireless Low-power System for Digital Identification of Examinees (Including Covid-19 Checks)
(2022)
Indoor localization has been, for the past decade, a subject under intense development. There is, however, no currently available solution that covers all possible scenarios. Received Signal Strength Indicator (RSSI) based methods, although the most widely researched, still suffer from problems due to environment noise. In this paper, we present a system using Bluetooth Low Energy (BLE) beacons attached to the desks to localize students in exam rooms and, at the same time, automatically register them for the given exam. By using Kalman Filters (KFs) and discretizing the location task, the presented solution is capable of achieving 100% accuracy within a distance of 45cm from the center of the desk. As the pandemic gets more controlled, with our lives slowly transitioning back to normal, there are still sanitary measures being applied. An example being the necessity to show a certification of vaccination or previous disease. Those certifications need to be manually checked for everyone entering the university’s building, which requires time and staff. With that in mind, the automatic check for Covid certificates feature is also built into our system.
The use of quantum processing units (QPUs) promises speed-ups for solving computational problems, in particular for discrete optimisation. While a few groundbreaking algorithmic approaches are known that can provably outperform classical computers, we observe a scarcity of programming abstractions for constructing efficient quantum algorithms. A good fraction of the literature that addresses solving concrete problems related to database management concentrates on casting them as quadratic unconstrained binary optimisation problems (QUBOs), which can then, among others, be processed on gate-based machines (using the quantum approximate optimisation algorithm), or quantum annealers. A critical aspect that affects efficiency and scalability of either of these approaches is how classical data are loaded into qubits, respectively how problems are encoded into QUBO representation. The effectiveness of encodings is known to be of crucial importance for quantum computers, especially since the amount of available qubits is strongly limited in the era of noisy, intermediate-size quantum computers.
In this paper, we present three encoding patterns, discuss their impact on scalability, and their ease of use. We consider the recreational (yet computationally challenging) Sudoku problem and its reduction to graph colouring as an illustrative example to discuss their individual benefits and disadvantages. Our aim is enable database researchers to choose an appropriate encoding scheme for their purpose without having to acquire in-depth knowledge on quantum peculiarities, thus easing the path towards applying quantum acceleration on data management systems.
The digitization of almost all sectors of life and the quickly growing complexity of interrelationships between actors in this digital world leads to a dramatically increasing attack surface regarding both direct and also indirect attacks over the supply chain. These supply chain attacks can have different characters, e.g., vulnerabilities and backdoors in hardware and software, illegitimate access by compromised service providers, or trust relationships to suppliers and customers exploited in the course of business email compromise. To address this challenge and create visibility along these supply chains, threat-related data needs to be rapidly exchanged and correlated over organizational borders. The publicly funded project MANTRA is meant to create a secure and resilient framework for real-time exchange of cyberattack patterns and automated, contextualized risk management. The novel graph-based approach provides benefits for automation regarding cybersecurity management, especially when it comes to prioriization of measures for risk reduction and during active defense against cyberattacks. In this paper, we outline MANTRA’s scope, objectives, envisioned scientific approach, and challenges.
Abstraction layers are of paramount importance in software architecture, as they shield the higher-level formulation of payload computations from lower-level details. Since quantum computing (QC) introduces many such details that are often unaccustomed to computer scientists, an obvious desideratum is to devise appropriate abstraction layers for QC. For discrete optimisation, one such abstraction is to cast problems in quadratic unconstrained binary optimisation (QUBO) form, which is amenable to a variety of quantum approaches. However, different mathematically equivalent forms can lead to different behaviour on quantum hardware, ranging from ease of mapping onto qubits to performance scalability. In this work, we show how using higher-order problem formulations (that provide better expressivity in modelling optimisation tasks than plain QUBO formulations) and their automatic transformation into QUBO form can be used to leverage such differences to prioritise between different desired non-functional properties for quantum optimisation. Based on a practically relevant use-case and a graph-theoretic analysis, we evaluate how different transformation approaches influence widely used quantum performance metrics (circuit depth, gates count, gate distribution, qubit scaling), and also consider the classical computational efforts required to perform the transformations, as they influence possibilities for achieving future quantum advantage. Furthermore, we establish more general properties and invariants of the transformation methods. Our quantitative study shows that the approach allows us to satisfy different trade-offs, and suggests various possibilities for the future construction of general-purpose abstractions and automatic generation of useful quantum circuits from high-level problem descriptions.
Quantum software is becoming a key enabler for applying quantum computing to industrial use cases. This poses challenges to quantum software engineering in providing efficient and effective means to develop such software. Eventually, this must be reliably achieved in time, on budget, and in quality, using sound and well-principled engineering approaches. Given that quantum computers are based on fundamentally different principles than classical machines, this raises the question if, how, and to what extent established techniques for systematically engineering software need to be adapted. In this chapter, we analyze three paradigmatic application scenarios for quantum software engineering from an industrial perspective. The respective use cases center around (1) optimization and quantum cloud services, (2) quantum simulation, and (3) embedded quantum computing. Our aim is to provide a concise overview of the current and future applications of quantum computing in diverse industrial settings. We derive presumed challenges for quantum software engineering and thus provide research directions for this emerging field.
Federated online social networks are an alternative to centralized and often profit-driven social networks. Instead of providing exactly one main platform, federated and decentralized approaches consist of multiple platforms, nodes or instances, leading to new challenges for guaranteeing confidentiality, integrity and availability. In addition, privacy is taken into close consideration due to the sensitive nature of processed personal data and the purpose of online social networks as well as the user behavior on social media. The recent popularity and broad use of the federated micro-blogging platform Mastodon issues the matter of security and privacy challenges for this type of architecture and the specific platform as well. Mastodon is part of a larger network called Fediverse with several platforms with different purposes. Communication and interoperability between Fediverse platforms is mostly achieved by ActivityPub protocol as standard for decentralized social networking, defined by W3C. We analyze Mastodon as the currently most prominent and largest example of a Fediverse platform. Therefore, we perform tests for typical types of software vulnerabilities as well as evaluate common security challenges built into its design. As a result, we identify trust as security principle as critical issue, leading to multiple weak points such as enabling attackers and malicious actors to spread misleading information as well as network availability impacts. We suggest possible solutions customized to our findings as well as general security recommendations when building a federated online social network such as the Fediverse
Distributed Denial of Service attacks are among the most common and widespread network attacks. Due to their nature, they are difficult to defend. Intrusion detection systems, based on machine learning, are a promising approach to counter this threat. But to train these systems, data sets with Distributed Denial of Service attacks are needed. An implemented Python program, which creates Denial of Services packets and simulates distributed sending by multithreading, is presented. Unlike synthetically generated data with the use of simulators, real network traffic is generated. This eliminates errors and offers a better basis of data, as machine learning algorithms need data that is as error-free as possible in order to learn efficiently.
Besides application fields such as entertainment and marketing, the technology of Virtual Reality is also applied in research and practice, including domains such as automotive, architecture, and construction. Furthermore, VR has been utilized for several activities in design practice and design research. However, the impact of this technology on design as a profession remains to be investigated. Thus, in the present study, an integrative literature review is presented to investigate the potential impact of Virtual Reality on design research and design practice. The findings indicate potential advantages on different levels. VR has the potential to enhance problem identification due to laboratorial environments and to foster co-creation due to enhanced motivation and the establishment of synergies between the involved stakeholders. Furthermore, it supports prototyping activities due to its capabilities for realistic scaling and perspectives. And lastly, VR has proven to be advantageous for design evaluations and reviews due to its visualization and immersion potential. Drawbacks of using VR for design research and practice involve technical limitations such as restricted field of view, limited performance, but also aspects such as missing accuracy for prototyping and the absence of haptic feedback. Future work will involve an extended review involving further literature and application domains.