A blockchain is redactable if a private key holder (e.g. a central authority) can change any single block without violating integrity of the whole blockchain, but no other party can do that. In this paper, we offer a simple method of constructing redactable blockchains inspired by the ideas underlying the well-known RSA encryption scheme. Notably, our method can be used in conjunction with any reasonable hash function that is used to build a blockchain. Public immutability of a blockchain in our construction is based on the computational hardness of the RSA problem and not on properties of the underlying hash function. Corruption resistance is based on the computational hardness of the discrete logarithm problem.
The research purposed would explain, not the bitcoin-blockchain (BTC-BC) phenomenon per se, considering a good level of knowledge on the themes, but focusing the attention on two implicit connotations that these “disruptive technologies” involve. The investigation conducted by the authors considers a sentiment analysis on news titles influence during the period 2015-2018 supported by a field analysis. That approach based on framing activity would intersect different study areas from innovation, economics, psychology, behavioral analysis, marketing and decision-making. Innovations should be studied under different aspects considering their probable wide range impacts on several fields. The exploratory approach to investigate something new would be interesting and useful to open windows of discussion and interpretation. The research focuses the two main factors of marketing strategies: scarcity and persuasion. The aim would be to validate these concepts in BTC-BC phenomenon as a kind of implicit marketing strategy.
Regional autonomy as the beginning of decentralization has the urgency to be implemented for the progress of the State. Regional financial institutions often occur collusion triangles with regional heads so that they do not guarantee the implementation of good regional government because of the management of sub-optimal regional assets. The need for maximizing the functions of regional institutions so that regional assets can be managed for regional progress evenly. The absence of special regulations regarding the management of regional finance is a problem because it still uses state financial laws so that the recommendations that the authors recommend in the form of optimizing regional financial institutions in managing regional assets and the existence of special regulations that regulate in detail the management of regional assets. The method used in this study is a normative juridical legal research method. Keywords: Institutional Function, Regional Finances, Regional Assets
High frequency Bitcoin price series are often non-linear and non-stationary and hence forecasting the price of Bitcoin directly or by transformation using statistical models is subject to large errors. This paper presents an ensemble model using variational mode decomposition (VMD) and Generalized additive model (GAM) to forecast intraday Bitcoin price. To evaluate the performance of the constructed model, it is compared with an ensemble of empirical mode decomposition (EMD) and GAM. The results showed that VMD-GAM model performed better than the EMD-GAM ensemble model in terms of three evaluation metrics (root mean square error, mean absolute percentage error, and bias) used.
Konstantin D. Pandl, Scott Thiebes, Manuel Schmidt-Kraepelin, Ali Sunyaev
Developments in Artificial Intelligence (AI) and Distributed Ledger\nTechnology (DLT) currently lead to lively debates in academia and practice. AI\nprocesses data to perform tasks that were previously thought possible only for\nhumans. DLT has the potential to create consensus over data among a group of\nparticipants in uncertain environments. In recent research, both technologies\nare used in similar and even the same systems. Examples include the design of\nsecure distributed ledgers or the creation of allied learning systems\ndistributed across multiple nodes. This can lead to technological convergence,\nwhich in the past, has paved the way for major innovations in information\ntechnology. Previous work highlights several potential benefits of the\nconvergence of AI and DLT but only provides a limited theoretical framework to\ndescribe upcoming real-world integration cases of both technologies. We aim to\ncontribute by conducting a systematic literature review on previous work and\nproviding rigorously derived future research opportunities. This work helps\nresearchers active in AI or DLT to overcome current limitations in their field,\nand practitioners to develop systems along with the convergence of both\ntechnologies.\n
Blockchain technology, as a bedrock for distributed ledgers, offers a platform for innovation for a new decentralized and transparent transaction machinery in industries and businesses, and the port is not an exception. The inbuilt features of this technology enrich trust through transparency and traceability within any transaction of data, goods, services, and financial resources. Notwithstanding initial doubts about this technology, lately government and large corporations have offered to adopt and enhance this technology in various fields of applications, from social and legal industries, and finance to design, maritime and port networks. In this paper, the authors review the current status of the Blockchain technology and some of its applications. The potential benefit of such a technology in port and maritime supply chain is then discussed, and a vision for the future Blockchain ready port and maritime supply chain are proposed. The importation of containerized vehicles is used as an example to demonstrate how such technology can be deployed in a global port industry. Finally, the requirements and challenges to adopt this technology in the future in relation to, port and maritime systems are discussed.
The recent extreme volatility in cryptocurrency prices occurred in the setting of popular social media forums devoted to the discussion of cryptocurrencies. We develop a framework that discovers potential causes of phasic shifts in the price movement captured by social media discussions. This draws on principles developed in healthcare epidemiology where, similarly, only observational data are available. Such causes may have a major, one-off effect or recurring effects on the trend in the price series. We find a one-off effect of regulatory bans on bitcoin, the repeated effects of rival innovations on ether and the influence of technical traders, captured through discussion of market price, on both cryptocurrencies. The results for Bitcoin differ from Ethereum, which is consistent with the observed differences in the timing of the highest price and the price phases. This framework could be applied to a wide range of cryptocurrency price series where there exists a relevant social media text source. Identified causes with a recurring effect may have value in predictive modelling, whilst one-off causes may provide insight into unpredictable black swan events that can have a major impact on a system.
Christopher Klinkmüller, Ingo Weber, Alexander Ponomarev, An Binh Tran · 5 authors
Second generation blockchain platforms, like Ethereum, can store arbitrary data and execute user-defined smart contracts. Due to the shared nature of blockchains, understanding the usage of blockchain-based applications and the underlying network is crucial. Although log analysis is a well-established means, data extraction from blockchain platforms can be highly inconvenient and slow, not least due to the absence of logging libraries. To close the gap, we here introduce the Ethereum Logging Framework (ELF) which is highly configurable and available as open source. ELF supports users (i) in generating cost-efficient logging code readily embeddable into smart contracts and (ii) in extracting log analysis data into common formats regardless of whether the code generation has been used during development. We provide an overview of and rationale for the framework's features, outline implementation details, and demonstrate ELF's versatility based on three case studies from the public Ethereum blockchain.
Haiti announced in 2018 its aim to achieve universal health coverage. In this paper, we discuss what this objective means for the country and what next steps should be taken. To contextualize the notion, we framed Haiti en route to the 2030 goal and analyzed qualitatively the status quo in terms of geographic, financial, and service access. For each dimension, we focused on the context, the government's policies and political agendas, their implementation progress, and key influential factors. Our analysis found little progress and numerous challenges. Geographic access was limited due principally to the insufficient number of facilities, difficulties in reaching health facilities, and local customs. Financial coverage was low because of the government's insufficient budgets, inefficient budget allocation, and ineffective management. Service access also had room for significant improvement for a lack of basic infrastructure and resources, gaps between the essential service package guidelines, health professionals' skills, and the needs, as well as deficiencies in people-centered care. These factors affected not only health service coverage but also its quality. We found that the root causes of these issues were composed of unstable financing mechanisms, opportunistic resource allocation, and ineffective management control systems. We suggest that to overcome these issues and achieve universal health coverage with decent service quality, Haiti's health system needs to be reformed by implementing strategic financing, decentralized management systems, and community engagement in primary health care.
Stefan Tönnissen, Jan Heinrich Beinke, Frank Teuteberg
Abstract Start-ups in the blockchain context generate millions by means of initial coin offerings (ICOs). Many of these crowdfunding endeavours are very successful, others are not. However, despite the increasing investments in ICOs, there is still neither sufficient theoretical knowledge nor a comprehensive understanding of the different types of business models and the implications for these token-based ecosystems. Scientific research equally lacks a thorough understanding of the different business model forms and their influence on collaboration in token-based economies. We bridge this gap by presenting a taxonomy of real-world blockchain-based start-ups. For this taxonomy, we used 195 start-ups and performed a cluster-analysis in order to identify three different archetypes and thus gain a deeper understanding. Our taxonomy and the archetypes can equally be seen as strategic guidance for practitioners as well as a starting point for future research concerning the token-based business models.
Traditional centralized data storage and processing solutions manifest limitations with regards to overall operational cost and the security and auditability of data. One of the biggest issues with existing solutions is the difficulty of keeping track of who has had access to the data and how the data may have changed over its lifetime; while providing a secure and easy-to-use mechanism to share the data between different users. The ability to electronically regulate data sharing within and across different organizational entities in the supply chain (SC) is an open issue that is only addressed partially by existing legal and regulatory compliance frameworks. In this article, we present Cydon, a decentralized data management platform that executes bespoke distributed applications utilizing a novel search and retrieve algorithm leveraging metadata attributes. Cydon utilizes a smart distributed ledger to offer an immutable audit trail and transaction history for all different levels of data access and modification within a SC and for all data flows within the environment. Results suggest that Cydon provides authorized and fast access to secure distributed data, avoids single points of failure by securely distributing encrypted data across different nodes while maintains an “always-on” chain of custody.
Popular Blockchain-based cryptocurrencies, like Bitcoin, are increasingly being used maliciously for illegal trades. In order to trace and analyze suspected Bitcoin transactions and addresses, address clustering methods and Bitcoin flow analysis methods are gaining attention recently. However, existing methods only focus on Bitcoin addresses and flow, and neglect other important information, such as transaction structure and behavior features. In order to exploit all useful features of transactions, this paper proposes a Bitcoin transaction network analytic method for facilitating Blockchain forensic investigation based on an extended safe Petri Net. The structural features and dynamic semantics of Petri net are used in our proposed model to define the static and dynamic features of Bitcoin transactions. Nineteen features have been identified to define Bitcoin transaction patterns for analyzing and finding suspected addresses. Bitcoin gene has been embedded into the Petri net transitions to trace and analyze Bitcoin flow accurately. Finally, marginal distribution analysis of Bitcoin transaction features and data visualization techniques are used to eliminate some false positive samples further and to improve the accuracy of identifying suspected addresses. The proposed Bitcoin transaction network analytic method provides a reliable forensic investigation model along with a prototype platform which is beneficial for financial security. The efficiency of our proposed method is empirically verified based on a real-life case study analysis.
Bankacılık sektöründe blok zincir sistemleri alternatif bir bankalar arası para transferi platformu olarak araştırılmaktadır. Bununla birlikte, blockchain ağ yapısı henüz olgunlaşmamış ve potansiyeli de henüz tam olarak analiz edilmemiştir. Böyle bir sistemi tamamen işletmek için çözülmesi gereken birçok husus ve barındırdığı fırsatlar olabilir. Sınır ötesi ödeme sistemleri için blockchain kullanımı ile ilgili araştırmalar hızla ilerlemektedir; bu nedenle, bu alandaki ilerlemeyi sıklıkla değerlendirmek gerekmektedir. Bu ihtiyaca cevap vermek için, bu makalede, araştırma makaleleri ve vakalardan oluşan güncel literatür analiz edilerek sınır ötesi ödemeler için blockchain teknolojisinin kullanımının önemi tartışılmış ve bu alandaki ilerleme analiz edilmiştir
As a trending and interesting research topic, in recent years, researchers have been adopting the blockchain in the wireless ad-hoc environment. Owing to its strong characteristics, such as consensus, immutability, finality, and provenance, the blockchain is utilized not only as a secure data storage for critical data but also as a platform that facilitates the trustless exchange of data between independent parties. However, the main challenge of blockchain application in an ad-hoc network is which kind of nodes should be involved in the validation process and how to adopt the heavy computational complexity of block validation appropriately while maintaining the genuine characteristics of a blockchain. In this paper, we propose the blockchain-based trust management system with a lightweight consensus algorithm in a mobile ad-hoc network (MANET). The proposed scheme provides the distributed trust framework for routing nodes in MANETs that is tamper-proof via blockchain. The optimized link state routing protocol (OLSR) is exploited as a representative protocol to embed the blockchain concept in MANETs. As a securely distributed and trusted platform, blockchain solves most of the security issues in the OLSR, in which every node is performing the security operation individually and in a repetitive manner. Additionally, using predefined principles, the routing nodes in the proposed scheme can collaborate to defend themselves from the attackers in the network. The experimental results show that the proposed consensus algorithm is suitable to be used in the resource-hungry MANET with reduced validation time and less overhead. Meanwhile, the attack detection overhead and time also decrease because the repetitivity of the process is reduced while providing a scalable and distributed trust among the routing nodes.
Edi Pranyoto, Susanti Susanti, Septiyani Septiyani
The objective of this research was to determine the effect of the herding behavior and the experienced regret on the investment decision. The type of this research was quantitative research. The data collecting technique used in this research was distributing questionnaires. The sampling technique used in this research was the snowball sampling technique. The number of samples used in this research was 100 investor of bitcoin. The data analyzing technique used in this research was the multiple linear regression analysis. The result of this research showed that the herding behavior had no significant effects on the investment decision; moreover, the experienced regret had a positive and significant effect on the investment decision. It meant that the investors rationally received and analyzed information well in bitcoin because they were not affected by the other investors and did not follow the market situation. In addition, the experienced level of investor regret was considered higher on the condition that the investment decision was also higher because they had enough experience in making the investment decision. Keywords — Herding Behavior, Experienced Regret, Investment Decision, Bitcoin
Guevara Noriega, E. P. Toapanta Mejía, J. C. Daquilema Taco, D. R. Vallejo Altamirano
Los cambios constantes en el nivel de las organizaciones públicas hacen que estas expandan su visión y la competitividad permanente lleva a los Gobiernos Autónomos Descentralizados (GAD) Municipales a desarrollar estrategias para alcanzar sus objetivos, es así como, la contratación y la continuidad de los despidos del personal representa un problema de gran magnitud para las instituciones, pues sin duda, limita el desarrollo eficiente que se desearía tener, ya que la productividad de la institución se ve significativamente afectada, evidenciándose un mal clima organizacional, restando la eficiencia eficacia y efectividad en los procesos, influyendo directamente en los resultados Esta investigación determina un análisis de las causas del clima organizacional en una institución pública. Debido a la alta tasa de rotación evidenciada dentro de los municipios según se constata en las encuestas realizadas, principalmente en el personal operativo, que son aquellos que trabajan directamente con los usuarios y pueden tener los efectos causados por el servicio ofrecido. En consecuencia, esta investigación conlleva aumentar el servicio al usuario proporcionado por los colaboradores públicos. Y una relación muy estrecha entre el clima organizacional medido y la rotación de personar también se define al analizar la premisa de que si el clima organizacional mejora la rotación de personal se reducirá el malestar entre compañeros de trabajo, ya que puede haber razones que no se conocen o están fuera del control y, por lo tanto, no se pueden mejorar el lineamiento de prestigio institucional. Constant changes at the level of public organizations mean that they expand their vision and permanent competitiveness leads the Municipal Autonomous Decentralized Governments (GAD) to develop strategies to achieve their objectives, such as hiring and continuity of layoffs The staff represents a problem of great magnitude for the institutions, because without a doubt, it limits the efficient development that one would like to have, since the productivity of the institution is significantly affected, evidencing a bad organizational climate, subtracting the efficiency effectiveness and effectiveness in the processes, directly influencing the results This research determines an analysis of the causes of the organizational climate in a public institution. Due to the high rate of turnover evidenced within the municipalities as found in the surveys carried out, mainly in the operating personnel, which are those that work directly with users and can have the effects caused by the service offered. Consequently, this research entails increasing the user service provided by public collaborators. And a very close relationship between the measured organizational climate and the turnover of people is also defined when analyzing the premise that if the organizational climate improves staff turnover, discomfort among coworkers will be reduced, since there may be reasons that are not they know or are out of control and, therefore, the institutional prestige guidelines can not be improved. Palabras Clave: desempeño, talento humano, rotación, clima laboral, decisiones. Keywords: performance, human talent, rotation, labor climate, decisions.
The article considers the problematic issues of the functioning of cryptocurrency in Ukraine. The risks that provoke cryptocurrency as a tool for the money laundering and the financing terrorism in Ukraine are studied. The level of crime and the use of cryptocurrency in the sphere of money laundering are determined. Topical issues affecting the features of the detection and investigation of a crime are considered.<br> Anti-money laundering law of Ukraine openly conflate money laundering (which is concerned with source of funds) with terrorism financing (which is concerned with destination of funds) when regulating the financial system. Furthermore, FATF report on terrorism financing noted the importance of links between financial tools and wider counter-terrorist activity to combat terrorist financing.<br> Terrorism, being a socially dangerous and difficult to predict phenomenon, is changing its forms, methods, but the need for terrorist organizations to collect, move, and use money is always urgent. The legalization (laundering) of proceeds of crime, as well as the financing terrorism, poses a serious threat to national security of Ukraine and its financial system. The use of computer technologies to commit crimes increases their social security, generates new ways of committing them, and simplifies the very process of committing and masking their tracks. Cryptocurrencies are popular on the dark web because they provide a convenient method of obfuscating identities and transaction details. In addition, the absence of rules for exchanges and points of sale, the obligation to identify the e-wallet owner and a clear legal regulation of the use of cryptocurrencies in general, create favorable conditions for criminals. Investigation of such crimes creates considerable difficulties, given the lack of capabilities of law enforcement agencies from the current level of technological and software criminal activity. The author also found out the advantages of such a currency, which determine its use by criminals, and examined possible ways to counter and combat such crime.
Yang Zhao, Jun Zhao, Jiawen Kang, Zehang Zhang · 7 authors
An increasing amount of users' sensitive information is now being collected for analytics purposes. To protect users' privacy, differential privacy has been widely studied in the literature. Specifically, a differentially private algorithm adds noise to the true answer of a query to generate a noisy response. As a result, the information about the dataset leaked by the noisy output is bounded by the privacy parameter. Oftentimes, a dataset needs to be used for answering multiple queries (e.g., for multiple analytics tasks), so the level of privacy protection may degrade as more queries are answered. Thus, it is crucial to keep track of the privacy spending which should not exceed the given privacy budget. Moreover, if a query has been answered before and is asked again on the same dataset, we may reuse the previous noisy response for the current query to save the privacy cost. In view of the above, we design and implement a blockchain-based system for tracking and saving differential-privacy cost. Blockchain provides a distributed immutable ledger that records each query's type, the noisy response used to answer each query, the associated noise level added to the true query result, and the remaining privacy budget in our system. Furthermore, since the blockchain records the noisy response used to answer each query, we also design an algorithm to reuse previous noisy response if the same query is asked repeatedly. Specifically, considering that different requests of the same query may have different privacy requirements, our algorithm (via a rigorous proof) is able to set the optimal reuse fraction of the old noisy response and add new noise (if necessary) to minimize the accumulated privacy cost. Experimental results show that the proposed algorithm can reduce the privacy cost significantly without compromising data accuracy.