Platforms are important actors in contemporary cultural economic processes. They include social network sites, online content management systems, streaming media platforms, mobile communication infrastructures, supply chain logistics solutions, and cryptocurrencies. Analysis of platforms and their capitalization should take into account the ways they structure social practice as assets and the constitutive opacity of platforms as configured realities. It explores capitalization by focusing on the problems of counting people and things on platforms. Via a case study of the software repository platform [Github.com] (https://github.com), it analyzes how 'platform numbers’ participate in capitalization. It describes attempts to enumerate the elements of the platform by counting, mapping or listing them. The paper shows how attempts to enumerate people and things encounter forms of association, duplication, combination, imitation and configuration that are crucial to the ensemble but remain refractory to capitalization. It proposes configurative enumeration of the platform numbers as a way of conceptualizing these un-enacted excesses. In a configurative enumeration, the composition, the rhythms of imitation, variation and commutation, and constant relating, repairing and adjusting of configurations crucial to the ongoing formation of platforms come into view. Configurative enumerations engage the inventive realities of platformization, realities that precede and sometimes overflow their capitalization.
Payment channels secured with cryptocurrency as collateral enable users to make many transactions with few blockchain broadcasts. Networks of payment channels have emerged as a proposed solution to Bitcoin’s scaling problem. Since the proposal of the first payment channel network, the Lightning Network, alternatives promising significant improvements, such as the Sprites protocol, have been proposed. Without at-scale implementations to analyze in situ, it is difficult to make meaningful comparisons of payment channel network protocols. In order to bridge this gap, we introduce a new simulation framework that can be used to evaluate how different payment channel network protocols will perform in both the expected and worst cases. \n \nOur framework is generic and accommodates benchmarking across different variants of payment channel network protocols, network topologies, routing algorithms, and user behaviors. User spending behavior in our payment channel network simulator is generated based on behavioral modeling techniques used in credit card fraud research. Our simulation is the first payment channel network simulator to seed user behaviors with data from real-world credit card users. \n \nOur framework can be used to evaluate expected case performance and resiliency to attacks across different payment channel network protocols and routing algorithms. We demonstrate the utility of our framework through comparisons of the Lightning Network to Sprites. We also compare the proposed decentralized routing algorithm, Flare, to an ideal centralized routing algorithm. Our results reveal that if spending behaviors are similar to those of credit card users, scale-free network topologies achieve higher throughput and resiliency compared to small-world networks. We also confirm that the Sprites protocol enjoys numerous advantages over the Lightning Network including smaller durations, shorter path length payments, and greater resiliency, all of which are most significant in decentralized topologies using decentralized routing algorithms.
Zehui Xiong, Yang Zhang, Dusit Niyato, Ping Wang · 5 authors
Blockchain, as the backbone technology of the current popular Bitcoin digital currency, has become a promising decentralized approach for resource and transaction management. Although blockchain has been widely adopted in many applications, e.g., finance, healthcare, and logistics, its application in mobile environments is still limited. This is due to the fact that blockchain users need to solve preset proof-of-work puzzles to add new transactions to the blockchain. Solving the proof-of-work, however, consumes substantial resources in terms of CPU time and energy, which is not suitable for resource-limited mobile devices. To facilitate blockchain applications in future mobile Internet of Things systems, multiple access mobile edge computing appears to be an auspicious option to solve the proof-of-work puzzles for mobile users. We first introduce a novel concept of edge computing for mobile blockchain. Then, we introduce an economic approach for edge computing resource management. Moreover, a demonstrative prototype of mobile edge computing enabled blockchain systems is presented with experimental results to justify the proposed concept.
Nelson Bore, Samuel Karumba, Juliet Mutahi, Shelby S. Darnell · 6 authors
Several initiatives have been proposed to collect, report, and analyze data about school systems for supporting decision-making. These initiatives rely mostly on self-reported and summarized data collected irregularly and rarely. They also lack a single independent and systematic process to validate the collected data during its entire lifecycle. Furthermore, schools in developing countries still do not maintain complete and up-to-date school records. Due to these and other factors addressing the education challenges in those countries remains a high priority for local and international governments, donor and non-governmental agencies across the world. In this paper, we discuss our initial design, implementation, and evaluation of a blockchain-enabled School Information Hub (SIH) using Kenya's school system as a case study.
Zehui Xiong, Yang Zhang, Dusit Niyato, Ping Wang · 5 authors
Blockchain, as the backbone technology of the current popular Bitcoin digital currency, has become a promising decentralized data management framework. Although blockchain has been widely adopted in many applications (e.g., finance, healthcare, and logistics), its application in mobile services is still limited. This is due to the fact that blockchain users need to solve preset proof-of-work puzzles to add new data (i.e., a block) to the blockchain. Solving the proof of work, however, consumes substantial resources in terms of CPU time and energy, which is not suitable for resource-limited mobile devices. To facilitate blockchain applications in future mobile Internet of Things systems, multiple access mobile edge computing appears to be an auspicious solution to solve the proof-of-work puzzles for mobile users. We first introduce a novel concept of edge computing for mobile blockchain. Then we introduce an economic approach for edge computing resource management. Moreover, a prototype of mobile edge computing enabled blockchain systems is presented with experimental results to justify the proposed concept.
Der vorliegende Beitrag untersucht, inwiefern Kryptowahrungen zur Liberierung des Aktienkapitals zulassig sind. Das Handelsregisteramt des Kantons Zug hat bereits eine Sacheinlagegrundung mit der derzeit bekanntesten Kryptowahrung – Bitcoin – zugelassen. Im Handelsregister
des Kantons Schwyz wurde eine beabsichtigte Sachubernahme fur einen vereinbarten Erwerb eines Portfolios verschiedener Kryptowahrungen eingetragen. Weitere Handelsregisteranmeldungen sind dem Vernehmen nach pendent. Es stellt sich die Frage, ob Kryptowahrungen generell zur Liberierung des Aktienkapitals zugelassen werden konnen. Die Praxis beurteilt hierbei die Bewertbarkeit und die Verwertbarkeit von Kryptowahrungen als schwierig. Als weitere Schwierigkeit kommen regulatorische Unsicherheiten hinzu, da die Regulierung von Kryptowahrungen ein «Moving Target» darstellt. Diese Unsicherheiten konnen sich auf die Bewertbarkeit und die Verwertbarkeit der liberierten Einlage auswirken.
Blockchain technology can be utilized to improve gun control without changing existing laws. Firearm related mortality is at epidemic levels in the United States and not only has a significant impact upon public health, it also creates a large financial burden. Suicide is the most common way guns kill. Through better gun tracking and improved screening of high risk individuals, this technological advance in distributed ledger technology will improve background checks on individuals and tracing of guns used in crimes.
Healthcare complexity and costs can be decreased through the application of blockchain technology to medical records and insurance companies. Estonia has taken a leadership role in blockchain based services both in the commercial sector and in government. The Estonian government’s innovation strategy was to create GovTech partnerships to implement blockchain based technologies throughout the country, and become a global leader in the technology. Starting in 2011, just 3 years after Satoshi Nakamoto published the first description of distributed ledgers and blockchain technology, the Estonian Government started partnering with the private technology startup company Guardtime to use blockchains to secure public and internal records. Then in 2016, Estonia once again reinforced its global leadership in blockchain technology when it announced it would use blockchain technology to secure the health records of over a million citizens. Estonia’s systematic method of applying blockchain technologies through GovTech partnerships demnostrates how innovation is a process. Estonia also identified early the value of the blockchain as a disruptive platform innovation. The application of blockchain technology to healthcare is a radical innovation given that nearly all previous applications have been in the financial and legal sectors.
Purpose The purpose of this paper is to determine if Bitcoin transactions could be de-anonymised by analysing the Bitcoin blockchain and transactions conducted through the blockchain. In addition, graph analysis and the use of modern social media technology were examined to determine how they may help reveal the identity of Bitcoin users. A review of machine learning techniques and heuristics was carried out to learn how certain behaviours from the Bitcoin network could be augmented with social media technology and other data to identify illicit transactions. Design/methodology/approach A number of experiments were conducted and time was spend observing the network to ascertain how Bitcoin transactions work, how the Bitcoin protocol operates over the network and what Bitcoin artefacts can be examined from a digital forensics perspective. Packet sniffing software, Wireshark, was used to see whether the identity of a user is revealed when they set up a wallet via an online wallet service. In addition, a block parser was used to analyse the Bitcoin client synchronisation and reveal information on the behaviour of a Bitcoin node when it joins the network and synchronises to the latest blockchain. The final experiment involved setting up and witnessing a transaction using the Bitcoin Client API. These experiments and observations were then used to design a proof of concept and functional software architecture for searching, indexing and analyzing publicly available data flowing from the blockchain and other big data sources. Findings Using heuristics and graph analysis techniques show us that it is possible to build up a picture of behaviour of Bitcoin addresses and transactions, then utilise existing typologies of illicit behaviour to collect, process and exploit potential red flag indicators. Augmenting Bitcoin data, big data and social media may be used to reveal potentially illicit financial transaction going through the Bitcoin blockchain and machine learning applied to the data sets to rank and cluster suspicious transactions. Originality/value The development of a functional software architecture that, in theory, could be used to detect suspicious illicit transactions on the Bitcoin network.
In this work, we propose a straightforward method to derive Elliptic Curve Digital Signature Algorithm (ECDSA) key pairs from embeddings created using Deep Learning and Metric Learning approaches. We also show that these keys allows the derivation of cryptocurrencies (such as Bitcoin) addresses that can be used to transfer and receive funds, allowing novel Blockchain-based applications that can be used to transfer funds or data directly to domains such as image, text, sound or any other domain where Deep Learning can extract high-quality embeddings; providing thus a novel integration between the properties of the Blockchain-based technologies such as trust minimization and decentralization together with the high-quality learned representations from Deep Learning techniques.
Brian M. Till, Alexander W. Peters, Salim Afshar, John G. Meara
Blockchain technology and cryptocurrencies could remake global health financing and usher in an era global health equity and universal health coverage. We outline and provide examples for at least four important ways in which this potential disruption of traditional global health funding mechanisms could occur: universal access to financing through direct transactions without third parties; novel new multilateral financing mechanisms; increased security and reduced fraud and corruption; and the opportunity for open markets for healthcare data that drive discovery and innovation. We see these issues as a paramount to the delivery of healthcare worldwide and relevant for payers and providers of healthcare at state, national and global levels; for government and non-governmental organisations; and for global aid organisations, including the WHO, International Monetary Fund and World Bank Group.
Shehar Bano, Alberto Sonnino, Mustafa Al-Bassam, Sarah Azouvi · 7 authors
The blockchain initially gained traction in 2008 as the technology underlying bitcoin, but now has been employed in a diverse range of applications and created a global market worth over $150B as of 2017. What distinguishes blockchains from traditional distributed databases is the ability to operate in a decentralized setting without relying on a trusted third party. As such their core technical component is consensus: how to reach agreement among a group of nodes. This has been extensively studied already in the distributed systems community for closed systems, but its application to open blockchains has revitalized the field and led to a plethora of new designs. The inherent complexity of consensus protocols and their rapid and dramatic evolution makes it hard to contextualize the design landscape. We address this challenge by conducting a systematic and comprehensive study of blockchain consensus protocols. After first discussing key themes in classical consensus protocols, we describe: first protocols based on proof-of-work (PoW), second proof-of-X (PoX) protocols that replace PoW with more energy-efficient alternatives, and third hybrid protocols that are compositions or variations of classical consensus protocols. We develop a framework to evaluate their performance, security and design properties, and use it to systematize key themes in the protocol categories described above. This evaluation leads us to identify research gaps and challenges for the community to consider in future research endeavours.
Purpose The rise of cultural governance has made cultural democracy important in East Asia. South Korea and China have chosen to develop cultural democracy by means of developing community-based cultural houses. Cultural houses in Korea were first managed from the center but have now been decentralized, and those in China have been developed based on local financing and administration. Since central-local intergovernmental relations, as they relate to public culture, have gone untouched in East Asia, the purpose of this paper is to study how central-local intergovernmental relations have impacted the development of cultural democracy in this area, in order to better understand how public culture should be developed. Design/methodology/approach A comparative study of the cases of South Korea and China has been used. The materials and information collected for the study were gathered by a review and an analysis of extant literature, policy documents, data and other materials from the relevant departments of both countries. It was also based on semi-structured interviews conducted with the national cultural departments, regulatory institutions, and with officials and scholars. Findings This study shows that central-local intergovernmental relations can have an impact on the management of community-based cultural houses and the effectiveness of cultural democracy’s development. Only complete decentralization that directly invites democratization will provide positive local conditions for cultural democracy’s growth. In short, meaningful governmental responses to local demands and a strong civil society are critical for the advancement of cultural democracy. Practical implications This study seeks to provide insights into the relationship between central-local intergovernmental relations and cultural democracy. At the micro project level, cultural project management should be improved; at the medium local level, the public must be made part of any decentralization effort; and at the macro national level, the multiple impacts caused by decentralization need to be considered. Originality/value This study is unique in terms of both its research questions and its research area. Central-local intergovernmental relations, as they relate to public culture, have gone comparatively untouched, especially in the context of East Asia. It is in this context that studying how central-local intergovernmental relations impact the development of cultural democracy is worthwhile, in order to better understand how public culture has developed and will be developed in future. A comparative study of the cases of South Korea and China has been used to discover the impacts of different dimensions of central-local decentralization on cultural development.
Smart contracts are technically defined as an event-driven programs, with state, that run on a distributed, decentralized, shared and replicated ledger (blockchain) and that can take custody over and transfer assets on the ledger. This new invention enables declarations of will to be expressed as self-executing computer code. The fact that smart contracts can transfer assets without the need for judicial system creates many questions about their place in the civil law. Also, it raises a question about their legality. This paper explores some basic concepts related to smart contracts and tries to set boundaries to their legality in the framework of civil law in scope of form and interpretation.
Polina Mamoshina, Lucy O. Ojomoko, Yury Yanovich, Alex Ostrovski · 12 authors
// Polina Mamoshina 1,2 , Lucy Ojomoko 1 , Yury Yanovich 3 , Alex Ostrovski 3 , Alex Botezatu 3 , Pavel Prikhodko 3 , Eugene Izumchenko 4 , Alexander Aliper 1 , Konstantin Romantsov 1 , Alexander Zhebrak 1 , Iraneus Obioma Ogu 5 and Alex Zhavoronkov 1,6 1 Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, Maryland, USA 2 Department of Computer Science, University of Oxford, Oxford, United Kingdom 3 The Bitfury Group, Amsterdam, Netherlands 4 Department of Otolaryngology-Head & Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA 5 Africa Blockchain Artificial Intelligence for Healthcare Initiative, Insilico Medicine, Inc, Abuja, Nigeria 6 The Biogerontology Research Foundation, London, United Kingdom Correspondence to: Alex Zhavoronkov, email: // Keywords : artificial intelligence; deep learning; data management; blockchain; digital health Received : October 19, 2017 Accepted : November 02, 2017 Published : November 09, 2017 Abstract The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals.
Open access
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Blockchain Technology Applications and Security
Artificial Intelligence in Healthcare and Education
Blockchain has recently been applied in many applications such as bitcoin, smart grid, and Internet of Things (IoT) as a public ledger of transactions. However, the use of blockchain in mobile environments is still limited because the mining process consumes too much computing and energy resources on mobile devices. Edge computing offered by the Edge Computing Service Provider can be adopted as a viable solution for offloading the mining tasks from the mobile devices, i.e., miners, in the mobile blockchain environment. However, a mechanism needs to be designed for edge resource allocation to maximize the revenue for the Edge Computing Service Provider and to ensure incentive compatibility and individual rationality is still open. In this paper, we develop an optimal auction based on deep learning for the edge resource allocation. Specifically, we construct a multi-layer neural network architecture based on an analytical solution of the optimal auction. The neural networks first perform monotone transformations of the miners' bids. Then, they calculate allocation and conditional payment rules for the miners. We use valuations of the miners as the data training to adjust parameters of the neural networks so as to optimize the loss function which is the expected, negated revenue of the Edge Computing Service Provider. We show the experimental results to confirm the benefits of using the deep learning for deriving the optimal auction for mobile blockchain with high revenue
What is the first thing that comes to mind when you hear the word – Bitcoin? When asked this question, I got responses that were synonymous to “Easy New Money”. Cryptocurrencies like Bitcoin have garnered popularity over the last 5 years. So much so, that in 2012 one Bitcoin was valued around $10 but today, one Bitcoin is a whopping $4300, approximately. At its core, the cryptocurrency networks are decentralized systems, with 2 kinds of participants - account holders and miners. Whenever a transaction takes place between the account holders, miners maintain the integrity of the system by checking its validity. The miners then compete to solve a puzzle, which validate these transactions, called Proof-of-Work (PoW). The miner who solved the puzzle first is rewarded a Bitcoin for its effort. Until now all sounds rosy and too good to be true, so where is the problem? In order to solve this PoW, an enormous amount of computation is needed. Not to throw around statistics, but to emphasize the gravity of the situation - A study of the carbon footprint of the Bitcoin network in 2013, when one Bitcoin valued around $1000, claimed that the annual CO2 emissions of the network were comparable to that of the country Cyprus. Some even went to the extent of calling it “A Real-World Environmental Disaster”. The reason for such enormous computational cost is the continuous need to solve PoW puzzles, in order to defend the system against malicious participants called adversaries. My dissertation research is aimed at designing novel efficient PoW protocols/algorithms, which result in the computational cost to the system to be commensurate with those of the adversary. More precisely, if the network is attacked, we ensure security, with a cost that grows linearly with the attacker’s cost; and, in the absence of an attack, our computational cost remains small.
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