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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.
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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Innovative work behavior has been one of the essential attribute of high performing firms, and the roles of entrepreneurial orientation and self-leadership have been important for promoting innovative work behavior. This study advances research on innovative work behavior by examining the mediating role of self-leadership in the relationship between perceived entrepreneurial orientation and innovative work behavior. Structural equation modelling is employed to analyze data from a survey of 404 employees in banking sector. The results of reliability measures and confirmatory factor analysis strongly support the scale of the study. The results from an empirical survey study in the deposit banks reveal that participants’ perceptions about high levels of entrepreneurial orientation have a positive impact on innovative work behavior. The results also provide support for the full mediating role of self-leadership in the relationship between participants’ perceptions of entrepreneurial orientation and innovative work behavior. Additionally, this study provides some implications for practitioners in the banking sector to facilitate innovative work behavior through entrepreneurial orientation and self- leadership.
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.