Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf outlined an alternative to the current monetary system in which banks are replaced by a peer-to-peer system to issue and transfer digital money: the Bitcoin. While Bitcoin has attracted a substantial investment volume, the system has not achieved the status of a viable alternative monetary system. However, the distributed ledger technology (DLT) underlying the payment system is being applied successfully by financial institutions and is likely to have important implications for the future of money and banking. In this paper we therefore focus on the most advanced distributed ledger application in the financial industry: R3 Corda. This paper is structured as follows. In the first section, we relate the debate about systems of money creation to the rise of Bitcoin. Next, the development of R3 Corda is discussed and the lessons learned for monetary reform. We conclude with an assessment of the scope and likelihood of monetary reform as a consequence of DLT applications by central banks.
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Lawmakers as representatives of the people should resist the anti-competitive proposals of the banking sector and embrace a vision of the digital euro that serves the collective interests of Europeans, Dr Martijn van der Linden and Vicky Van Eyck write. The influence of the banking lobby on policymakers risks undermining the digital euro's potential. Lawmakers as representatives of the people should resist the anticompetitive proposals of the banking sector and embrace a vision of the digital euro that serves the collective interests of Europeans. This means that the digital euro must be attractive, accessible and beneficial to all. The deliberation process must be free from the disproportionate influence of an industry that has much to lose from a level playing field for payment services and financial intermediation.
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Purpose: Small and medium-sized entities (SMEs) operating in the alternative financing sector are typically heterogenous in nature making them differ greatly from traditional banks. Where traditional banks must comply with strict banking regulations, developing uniform regulations for the alternative financing sector remains a challenge. This paper examines the current challenges and solutions from a sociological and institutional perspective in developing standards for SMEs operating in the alternative financing sector in the Netherlands. Adopting minimum quality standards should lead to increased transparency and public trust in the non-banking sector.
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Today, embedded devices such as banking/transportation cards, car keys, and mobile phones use cryptographic techniques to protect personal information and communication. Such devices are increasingly becoming the targets of attacks trying to capture the underlying secret information, e.g., cryptographic keys. Attacks not targeting the cryptographic algorithm but its implementation are especially devastating and the best-known examples are so-called side-channel and fault injection attacks. Such attacks, often jointly coined as physical (implementation) attacks, are difficult to preclude and if the key (or other data) is recovered the device is useless. To mitigate such attacks, security evaluators use the same techniques as attackers and look for possible weaknesses in order to “fix” them before deployment. Unfortunately, the attackers’ resourcefulness on the one hand and usually a short amount of time the security evaluators have (and human errors factor) on the other hand, makes this not a fair race. Consequently, researchers are looking into possible ways of making security evaluations more reliable and faster. To that end, machine learning techniques showed to be a viable candidate although the challenge is far from solved. Our project aims at the development of automatic frameworks able to assess various potential side-channel and fault injection threats coming from diverse sources. Such systems will enable security evaluators, and above all companies producing chips for security applications, an option to find the potential weaknesses early and to assess the trade-off between making the product more secure versus making the product more implementation-friendly. To this end, we plan to use machine learning techniques coupled with novel techniques not explored before for side-channel and fault analysis. In addition, we will design new techniques specially tailored to improve the performance of this evaluation process. Our research fills the gap between what is known in academia on physical attacks and what is needed in the industry to prevent such attacks. In the end, once our frameworks become operational, they could be also a useful tool for mitigating other types of threats like ransomware or rootkits.
The hospitality industry in the Netherlands has been slow to adopt artificial intelligence (AI), despite its potential to improve service efficiency and address workforce challenges. While some industries have embraced AI agents—automated systems interacting with users—for customer service, hospitality adoption remains limited. Many hotels struggle to integrate AI in ways that enhance guest experiences while ensuring workforce sustainability, a paradox. Workforce sustainability means keeping employees skilled and adaptable. This research addresses this paradox observed in professional practice, focusing on three key gaps in AI integration: • Hotel employees lack the skills and knowledge to adapt to AI-enhanced workplaces. • Hotel managers lack clear AI strategies that maintain service quality and employee well-being, ensuring AI complements rather than replaces human service. • AI developers often lack a clear understanding of the hospitality industry’s specific needs, hindering the development of effective solutions. This leads to the central question: How can AI agents be co-developed by hotel professionals and technical experts to enhance service efficiency while supporting a sustainable hospitality workforce? A one-year KIEM project provides the ideal framework for an agile, practice-based investigation in real hospitality environments. The project will unfold in four phases: (1) co-developing conversational AI chatbots with hotel businesses and technology providers, (2) testing the chatbot integration in hotels, (3) evaluating the impact on service efficiency and workforce sustainability, and (4) initiating a community of AI agent practice in service industry. Conducted in collaboration with industry partners, the research ensures findings are directly applicable to real-world hospitality challenges. By bridging academic research and industry needs, this project will generate insights into AI-driven service innovations that benefit hotel operations, employees, and AI developers. Beyond hospitality, its findings will offer scalable strategies for responsible AI adoption in sectors like healthcare, banking, and retail, fostering a more sustainable future of work.
