Blockchain Papers

Timothy King, Dimitrios Koutmos

No abstract is available for this record.

Ayana T. Aspembitova, Ling Feng, Lock Yue Chew

Human behavior as they engaged in financial activities is intimately connected to the observed market dynamics. Despite many existing theories and studies on the fundamental motivations of the behavior of humans in financial systems, there is still limited empirical deduction of the behavioral compositions of the financial agents from a detailed market analysis. Blockchain technology has provided an avenue for the latter investigation with its voluminous data and its transparency of financial transactions. It has enabled us to perform empirical inference on the behavioral patterns of users in the market, which we explore in the bitcoin and ethereum cryptocurrency markets. In our study, we first determine various properties of the bitcoin and ethereum users by a temporal complex network analysis. After which, we develop methodology by combining k -means clustering and Support Vector Machines to derive behavioral types of users in the two cryptocurrency markets. Interestingly, we found four distinct strategies that are common in both markets: optimists, pessimists, positive traders and negative traders. The composition of user behavior is remarkably different between the bitcoin and ethereum market during periods of local price fluctuations and large systemic events. We observe that bitcoin (ethereum) users tend to take a short-term (long-term) view of the market during the local events. For the large systemic events, ethereum (bitcoin) users are found to consistently display a greater sense of pessimism (optimism) towards the future of the market.

Bello Musa Yakubu, Majid Iqbal Khan, Nadeem Javaid, Abid Khan

No abstract is available for this record.

Nisita Weerasinghe, Tharaka Hewa, Maheshi B. Dissanayake, Mika Ylianttila · 5 authors

Local 5G Operator (L5GO) concept is one of the most prominent versatile applications of the 5G in the near future. The popularity of L5GOs will trigger a greater number of roaming and offloading events between mobile operators. However, existing static and the operator-assisted roaming and offloading procedures are inefficient for L5GO ecosystem due to poor service quality, data privacy issues, data transferring delays, excessive costs for intermediary parties and existence of roaming fraud. To address these challenges, we propose a blockchain / Distributed Ledger Technology (DLT) based service platform for L5GOs to facilitate efficient roaming and offload services. As the key contribution, blockchain-based smart contract scheme is proposed to establish dynamic and automated agreements between operators. By using smart contracts, we introduce several novel features such as universal wallet for subscribers, service quality based L5GO rating system, user-initiated roaming process and the roaming fraud prevention system to improve the operational quality of a L5GO. A prototype of the proposed platform is emulated with the Ethereum blockchain platform and Rinkeby Testnet to evaluate the performance and justify the feasibility of the proposal. Upon an extensive evaluation on the prototype, it was observed that the proposed platform offered benefits such as cost effective, more secure and reliable experience.

Monir Shaker, Fereidoon Shams Aliee, Reza Fotohi

In most websites, the online rating system provides the ratings of products and services to users. Lack of trust in data integrity and its manipulation has hindered fulfilling user satisfaction. Since existing online rating systems deal with a central server, all rating data is stored on the central server. Therefore, all rating data can be removed, modified, and manipulated by the system manager to change the ratings in favor of the service or product provider. In this paper, an online rating system using distributed ledger technologies has been presented as the proposed system to solve all the weaknesses of current systems. Distributed ledger technologies are completely decentralized and there is no centralization on them by any institution. Distributed ledger technologies have different variants. Among distributed ledger technologies, blockchain technology has been used in the proposed rating system because of its support for smart contracts. In the proposed online rating system, the Ethereum platform has been chosen from different blockchain platforms that have a public permission network. In this system, the raters cannot rate unless they submit a request to the system and be authorized to take part in the online product rating process. The important feature of the Ethereum platform is its support for smart contracts, which can be used to write the rating contract in the Solidity language. Also, using Proof of Authority consensus mechanisms, all rating transactions are approved by the surveyors. Since in the real Ethereum system, each rating transaction is sent to the network by the raters, some gas must be paid for each rating transaction. However, since this method is expensive, TestNet blockchain can be used in the rating system. Finally, the proposed rating system was used for rating the restaurants of a website and its features were tested.

Nami Ashizawa, Naoto Yanai, Jason Paul Cruz, Shingo Okamura

Ethereum smart contracts are computer programs that are deployed and executed on the Ethereum blockchain to enforce agreements among untrusting parties. Being the most prominent platform that supports smart contracts, Ethereum has been targeted by many attacks and plagued by security incidents. Consequently, many smart contract vulnerabilities have been discovered in the past decade. To detect and prevent such vulnerabilities, different security analysis tools, including static and dynamic analysis tools, have been created, but their performance decreases drastically when codes to be analyzed are constantly being rewritten. In this paper, we propose Eth2Vec, a machine-learning-based static analysis tool that detects smart contract vulnerabilities. Eth2Vec maintains its robustness against code rewrites; i.e., it can detect vulnerabilities even in rewritten codes. Other machine-learning-based static analysis tools require features, which analysts create manually, as inputs. In contrast, Eth2Vec uses a neural network for language processing to automatically learn the features of vulnerable contracts. In doing so, Eth2Vec can detect vulnerabilities in smart contracts by comparing the similarities between the codes of a target contract and those of the learned contracts. We performed experiments with existing open databases, such as Etherscan, and Eth2Vec was able to outperform a recent model based on support vector machine in terms of well-known metrics, i.e., precision, recall, and F1-score.

Hanlin Zhang, Le Tong, Jia Yu, Jie Lin

Bilinear pairing is a fundamental operation that is widely used in cryptographic algorithms (e.g., identity-based cryptographic algorithms) to secure IoT applications. Nonetheless, the time complexity of bilinear pairing is$O(n^{3})$, making it a very time-consuming operation, especially for resource-constrained IoT devices. Secure outsourcing of bilinear pairing has been studied in recent years to enable computationally weak devices to securely outsource the bilinear pairing to untrustworthy cloud servers. However, the state-of-art algorithms often require to precompute and store some values, which results in storage burden for devices. In the Internet of Things, devices are generally with very limited storage capacity. Thus, the existing algorithms do not fit the IoT well. In this article, we propose a secure outsourcing algorithm of bilinear pairings, which does not require precomputations. In the proposed algorithm, the outsourcer side’s efficiency is significantly improved compared with executing the original bilinear pairing operation. At the same time, the privacy of the input and output is ensured. Also, we apply the Ethereum blockchain in our outsourcing algorithm to enable fair payments, which ensures that the cloud server gets paid only when he correctly accomplished the outsourced work. The theoretical analysis and experimental results show that the proposed algorithm is efficient and secure.

Hanlin Zhang, Peng Gao, Jia Yu, Jie Lin · 5 authors

Linear Regression (LR) is a classical machine learning algorithm which has many applications in the cyber physical social systems (CPSS) to shape and simplify the way we live, work and communicate. This paper focuses on the data analysis for CPSS when the Linear Regression is applied. The training process of LR is time-consuming since it involves complex matrix operations, especially when it gets a large scale training dataset In the CPSS. Thus, how to enable devices to efficiently perform the training process of the Linear Regression is of significant importance. To address this issue, in this paper, we present a secure, verifiable and fair approach to outsource LR to an untrustworthy cloud-server. In the proposed scheme, computation inputs/outputs are obscured so that the privacy of sensitive information is protected against cloud-server. Meanwhile, computation result from cloud-server is verifiable. Also, fairness is guaranteed by the blockchain, which ensures that the cloud gets paid only if he correctly performed the outsourced workload. Based on the presented approach, we exploited the fair, secure outsourcing system on the Ethereum blockchain. We analysed our presented scheme on theoretical and experimental, all of which indicate that the presented scheme is valid, secure and efficient.

Hélder Sebastião, Pedro Godinho

This study examines the predictability of three major cryptocurrencies-bitcoin, ethereum, and litecoin-and the profitability of trading strategies devised upon machine learning techniques (e.g., linear models, random forests, and support vector machines). The models are validated in a period characterized by unprecedented turmoil and tested in a period of bear markets, allowing the assessment of whether the predictions are good even when the market direction changes between the validation and test periods. The classification and regression methods use attributes from trading and network activity for the period from August 15, 2015 to March 03, 2019, with the test sample beginning on April 13, 2018. For the test period, five out of 18 individual models have success rates of less than 50%. The trading strategies are built on model assembling. The ensemble assuming that five models produce identical signals (Ensemble 5) achieves the best performance for ethereum and litecoin, with annualized Sharpe ratios of 80.17% and 91.35% and annualized returns (after proportional round-trip trading costs of 0.5%) of 9.62% and 5.73%, respectively. These positive results support the claim that machine learning provides robust techniques for exploring the predictability of cryptocurrencies and for devising profitable trading strategies in these markets, even under adverse market conditions.

Faiza Loukil, Chirine Ghédira, Khouloud Boukadi, Benharkat Aïcha-Nabila · 5 authors

The Internet of Things (IoT) is expected to improve the individuals’ quality of life. However, ensuring security and privacy in the IoT context is a non-trivial task due to the low capability of these connected devices. Generally, the IoT device management is based on a centralized entity that validates communication and connection rights. Therefore, this centralized entity can be considered as a single point of failure. Yet, in the case of distributed approaches, it is difficult to delegate the right validation to IoT devices themselves in untrustworthy IoT environments. Fortunately, the blockchain may provide decentralization of overcoming the trust problem while designing a privacy-preserving system. To this end, we propose a novel privacy-preserving IoT device management framework based on the blockchain technology. In the proposed system, the IoT devices are controlled by several smart contracts that validate the connection rights according to the privacy permission settings predefined by the data owners and the stored record array of detected misbehavior of each IoT device. In fact, smart contracts can immediately detect the devices that have vulnerabilities and have been hacked or pose a threat to the IoT network. Therefore, the data owner’s privacy is preserved by enforcing the control over the own devices. For validation purposes, we deploy the proposed solution on a private Ethereum blockchain and give the performance evaluation.

Vladislav Stanislavskyi

Investing in cryptoassets can be tricky. At the moment, there are many different cryptocurrencies operating on different blockchains with different ecosystems. The use of cryptoassets requires defining a goal in relation to the type of cryptoassets and the degree to which their properties affect their functioning and development. In this article, the author analyzes two of the most popular and significant cryptocurrencies for the cryptoindustry Bitcoin and Ethereum on two different blockchains. The author specifically took two cryptocurrencies that are completely different in their meaning and purpose. In view of the fact that the author does not see an ideal solution to several problems, he described the need for diversification of assets by purpose of use. The author describes each cryptocurrency as a separate ecosystem with its own properties, which requires playing by the rules. The author cites socio-economic factors due to which he chose these two blockchains for analysis, tries to analyze the dependence of the properties of each cryptocurrency on the level of popularization, and gives empirical data stating the consequences in a historical context.The author also considers technical properties as a factor of scalability and attractiveness of each of the blockchains, how cryptocurrencies interact with each other, influencing the financial mood of users. The author of the article also tries to determine the technical and social factors that led to the adaptation of these cryptocurrencies to the traditional financial sector and how they depend on each other. The author describes Bitcoin as a system for saving and multiplying funds, while Ethereum sees it as an ecosystem, an intermediary protocol between already formed market sectors and decentralized applications within the network. After analyzing the results of the study, the author provides general criteria for the formation of a methodology for choosing a cryptocurrency and blockchain for conducting effective operational activities, as well as the formation of its own mechanism for managing the efficiency of cryptocurrency operations.

Щербіна Марія Сергіївна

В даній дипломній роботі було досліджено існуючі системи та технології, що дозволяють проводити обмін токенами різних блокчейнів атомарно, розроблено та описано алгоритм проведення атомарного обміну криптовалютами, розроблено хешовані смарт-контракти з часовою затримкою для мереж Bitcoin та Ethereum, розроблено інтерактивну систему, що дозволяє провести атомарний обмін криптовалютами. Результатом дипломної роботи є програмне забезпечення для проведення атомарного обміну криптовалютами для токенів мереж Bitcoin та Ethereum.

Tatja Kärkkäinen

The four essays contained herein this study focus on recently emerged questions in the field of Financial Technology (FinTech). This new finance domain has a growing importance in the finance discipline, policy, and practice. The FinTech is the common theme, while the thesis is organised to investigate the open questions separately in the essays. The first essay assesses the required human capital in FinTech. Recent technological developments have enabled a wide array of new applications in financial markets, e.g. big data, cloud computing, artificial intelligence, blockchain, cryptocurrencies, peer-to-peer lending, crowdfunding, and robo-advising, inter alia. While traditionally comprising of computer programs and other technology used to support or enable banking and financial services, the new FinTech is often seen as enabling transformation of the financial industry. A more moderate and critical view suggests that for the full transformative potential of FinTech to be enabled, there is a need for an updated educational curriculum that balances knowledge and understanding of finance and technology. A curriculum that provides a skill portfolio in these two core components and complements them with applied knowledge. This essay also makes an inquiry into the educational curriculum in finance and technology, aiming to inform this modern educational agenda, and into the skills shortages, as identified by firms and experts with examining some of the first educational programmes in FinTech. The second essay investigates the relationship between financial literacy and attitudes to cryptocurrencies, using microdata from 15 countries. The financial literacy proxy exerts a large negative effect on the probability of currently owning cryptocurrencies. The financially literate are also more likely to be aware of cryptocurrencies, and less to own them due to their price volatility. In addition, data from a second survey of retail investors in three Asian countries is used to externally validify the financial literacy proxy and findings. I show that the relationship between financial literacy and attitudes to cryptocurrencies is moderated by a different perception of the financial risk involved in cryptocurrencies versus traditional investments by the more financially literate. The findings shed light on the demand for cryptocurrencies among the general population and suggest has been largely driven by unsophisticated investors. The third and fourth essays are closer in their empirical investigation of asset price timeseries data. In the third essay, I assess the bitcoin futures introduction into the retail investor driven marketplace. Bitcoin futures were introduced in December 2017 as an effort to provide institutional and retail investors with additional trading tools for bitcoin. This study analyses the bitcoin Futures mid-quote data from CBOE, and Bitcoin market index applying VAR and VECM process methodologies, Hasbrouck’s information share and the Gonzalo-Granger component share measurement to examine price discovery in bitcoin markets. The results drawn on the intra-day prices show that the futures are leading the price discovery at different frequencies even with comparably low futures trading volumes. The empirical results support the extant literature of futures-spot market price discovery and the role of informed traders in the futures market. Finally, the fourth essay attempts to evidence the network externalities on digital assets using exchange-listed Initial Coin Offerings (ICOs) data. Utilising an online database comprising of self-reported ICO characteristics, measures of post-ICO performance, along with information on business social networks, higher fundraising figures are found to contribute positively to the ICO long-term success. This positive impact is multiplied by six times when fundraising is conducted to an existing, proprietary blockchain. This large impact is explained by the network effect. The modified information ratio measure is introduced to approximate the comparative quality signalling of ICO organisations using price timeseries and benchmarking these to already functioning blockchain technology, e.g. ethereum in the long-term. The ICO sample’s mean trading period on an exchange is 1.5 years and is used for long-period asset analysis. Additionally, the cointegration to the market technology benchmark is found to have a large, significant negative effect on long-term ICO organisational success as this indicates lower ICO intrinsic value. The final concluding chapter summarises the thesis contribution, implications and a selection of future research avenues relating to FinTech research sub-field.

S. Gogia, Ujjwal Sharma

The COVID-19 pandemic has had a two-pronged effect -health and economy. Economies worldwide have been impacted and forced to shut during the lockdowns. In India, SMEs had already been struggling to stay afloat due to absence of financing, creating an inadequate cash flow. With frequent lockdowns, the situation has worsened, making bank loan applications difficult. This paper explores P2P lending in the context of micro-loans using a blockchain-powered solution to provide the necessary funds in a quick, easy, secure and contactless manner. As part of our Proof-of-Concept, a peer-to-peer decentralized Web Application is setup, utilizing the services of the Ethereum blockchain.

Neha S Aswale

No abstract is available for this record.

Raúl Riesco Granadino, Xavier Larriva-Novo, Víctor A. Villagrá

Although cyber threat intelligence (CTI) exchange is a theoretically useful technique for improving security of a society, the potential participants are often reluctant to share
\ntheir CTI and prefer to consume only, at least in voluntary based approaches. Such behavior destroys the idea of information exchange. On the other hand, governments are forcing specific entities and operators to report them specific incidents depending
\non their impact. Obligations and sanctions are usually discouraging participants to share information voluntarily. We propose a paradigm shift of cybersecurity information exchange by ntroducing a new way to encourage all participants involved, at
\nall levels, to share relevant information dynamically. Participants will have new and specific incentives to share, invest and consume threat intelligence and risk intelligence information depending on their different roles (producers, consumers, investors, donors and owner). Our proposal leverages from standards like Structured Threat Information Exchange (STIX™), W3C semantic web standards and from the Ethereum Blockchain to enable a workspace of knowledge related to behavioral threat intelligence patterning to characterize tactics, techniques and procedures (TTP) introducing new type of incentives.

Stefan Dziembowski, Grzegorz Fabiański, Sebastian Faust, Siavash Riahi

Blockchain is a disruptive new technology introduced around a decade ago. It can be viewed as a method for recording timestamped transactions in a public database. Most of blockchain protocols do not scale well, i.e., they cannot process quickly large amounts of transactions. A natural idea to deal with this problem is to use the blockchain only as a timestamping service, i.e., to hash several transactions tx_1,…,tx_m into one short string, and just put this string on the blockchain, while at the same time posting the hashed transactions tx_1,…,tx_m to some public place on the Internet ("off-chain"). In this way the transactions tx_i remain timestamped, but the amount of data put on the blockchain is greatly reduced. This idea was introduced in 2017 under the name Plasma by Poon and Buterin. Shortly after this proposal, several variants of Plasma have been proposed. They are typically built on top of the Ethereum blockchain, as they strongly rely on so-called smart contracts (in order to resolve disputes between the users if some of them start cheating). Plasmas are an example of so-called off-chain protocols. In this work we initiate the study of the inherent limitations of Plasma protocols. More concretely, we show that in every Plasma system the adversary can either (a) force the honest parties to communicate a lot with the blockchain, even though they did not intend to (this is traditionally called mass exit); or (b) an honest party that wants to leave the system needs to quickly communicate large amounts of data to the blockchain. What makes these attacks particularly hard to handle in real life is that these attacks do not have so-called uniquely attributable faults, i.e. the smart contract cannot determine which party is malicious, and hence cannot force it to pay the fees for the blockchain interaction. An important implication of our result is that the benefits of two of the most prominent Plasma types, called Plasma Cash and Fungible Plasma, cannot be achieved simultaneously. Besides of the direct implications on real-life cryptocurrency research, we believe that this work may open up a new line of theoretical research, as, up to our knowledge, this is the first work that provides an impossibility result in the area of off-chain protocols.

Tatja Kärkkäinen

No abstract is available for this record.

Shreya Bilonikar, Carol Mendonca, Divita Phadakale, Monali Shetty

No abstract is available for this record.

Bruce Masama, JP Bruwer

No abstract is available for this record.

Mohammad Hossin shafiabadi, Mohammad Hossin shafiabadi

The purpose of the present research was to introduce a blockchain-based voting system so that any state, including totalitarian states, can show interest in using it. In this method, a hybrid voting system with two centralized and distributed systems was used. Its centralized system is one of the most common voter identification and polling models, and its distributed system, which is designed with Ethereum public blockchain, is voting for voters. Totalitarian states are not interested in announcing the results online. Also, the lack of trust in E-voting systems by both states and voters has led to E-voting in important political elections in most states as support for manual or paper voting. Based on the results of field research with this voting system, it was possible to create a 7 min break between the end of the voting process and the announcement of the results for political considerations. This break can be increased by agreement. The results of the votes cannot be manipulated in any way. Survey results should also be communicated to voters before the voting process. This voting system can improve the level of democracy and maximum participation. It is hoped that the spread of distributed technologies, especially the blockchain, will pave the way for the spread of justice and democracy around the world.

<p>Enwei Liang</p>

This paper studies cryptocurrency. Firstly, this paper discusses the currency attribute of cryptocurrency. Secondly, this paper analyzes the advantages and disadvantages of cryptocurrency. Thirdly, this paper discusses the impact of cryptocurrency on the currency structure. Finally, this paper constructs the returns according to the daily price and statistically analyzes the yield difference of Bitcoin, Ethereum and Dogecoin. The ARIMA model is used to predict the return of cryptocurrency. This paper also gives the corresponding investment suggestions.

Mahsa Moosavi, Jeremy Clark

No abstract is available for this record.

Orla Nicole Hadjisophocleous, Tahir Abbas Syed, Hana Lee

While there is a rise in the applications of Blockchain technology in humanitarian and development aid programs, our understanding of Blockchain implementation and the resulting implications remains scant in this context. This research-in-progress report on the research currently underway in the United Nations World Food Program–Building Blocks. Adopting a case study approach, this study explores how the Building Block project revolutionizes the aid programs with the application of Ethereum, a blockchain-based distributed computing platform, and what new risk and social problems perpetuate with it. The study contributes to the growing stream of Information Systems research that focuses on the virtues and vices of using Blockchain technology and enhancing the effectiveness of humanitarian aid programs. As a relatively new technology, this study assesses the appropriateness of its usage and intends to provide insights to humanitarian and development organizations to consider when employing this novel technology.