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13,493 results · page 405 of 563
Yunting Yao, Ciwei Gao, Tao Chen, Jianlin Yang · 5 authors
No abstract is available for this record.
Dorsa Mohammadi Arezooji
First, a big data analysis of the transactions and smart contracts made on\nthe Ethereum blockchain is performed, revealing interesting trends in motion.\nNext, these trends are compared with the public's interest in Ether and\nBitcoin, measured by the volume of online searches. An analysis of the crypto\nprices and search trends suggests the existence of big players (and not the\nregular users), manipulating the market after a drop in prices. Lastly, a\ncross-correlation study of crypto prices and search trends reveals the pairs\nproviding more accurate and timely predictions of Ether prices.\n
Samuel Asumadu Sarkodie, Maruf Yakubu Ahmed, Phebe Asantewaa Owusu
The COVID-19 global pandemic has disrupted business-as-usual, hence, affecting sustained economic development across countries. However, it appears economic uncertainty following COVID-19 containment measures favor market signals of cryptocurrencies. Here, this study empirically and structurally investigates the implication of COVID-19 health outcomes on market prices of Bitcoin, Bitcoin Cash, Ethereum, and Litecoin. Evidence from the novel Romano-Wolf multiple hypotheses reveal COVID-19 shocks spur Litecoin by 3.20-3.84%, Bitcoin by 2.71-3.27%, Ethereum by 1.43-1.75%, and Bitcoin Cash by 1.34-1.62%.
Hyeong Joon Kim, Hye Hyeon Kim, Hosuk Ku, Kyung Don Yoo · 11 authors
BACKGROUND: ) for data privacy and participatory medicine; however, its fully decentralized architecture has come at the expense of decentralized data management and data provenance. OBJECTIVE: The introduction of blockchain and smart contract technologies to the legacy Health Avatar Platform with a clinical metadata registry remarkably strengthens decentralized health data integrity and immutable transaction traceability at the corresponding data-element level in a privacy-preserving fashion. A crypto-economy ecosystem was built to facilitate secure and traceable exchanges of sensitive health data. METHODS: The Health Avatar Platform decentralizes patient data in appropriate locations (ie, on patients' smartphones and on physicians' smart devices). We implemented an Ethereum-based hash chain for all transactions and smart contract-based processes to guarantee decentralized data integrity and to generate block data containing transaction metadata on-chain. Parameters of all types of data communications were enumerated and incorporated into 3 smart contracts, in this case, a health data transaction manager, a transaction status manager, and an application programming interface transaction manager. The actual decentralized health data are managed in an off-chain manner on appropriate smart devices and authenticated by hashed metadata on-chain. RESULTS: Metadata of each data transaction are captured in a Health Avatar Platform blockchain node by the smart contracts. We provide workflow diagrams each of the 3 use cases of data push (from a physician app or an intelligent agents to a patient Avatar), data pull (request to a patient Avatar by other entities), and data backup transactions. Each transaction can be finely managed at the corresponding data-element level rather than at the resource or document levels. Hash-chained metadata support data element-level verification of data integrity in subsequent transactions. Smart contracts can incentivize transactions for data sharing and intelligent digital health care services. CONCLUSIONS: Health Avatar Platform and interconnected patient Avatars, physician apps, and intelligent agents provide a decentralized blockchain ecosystem for health data that enables trusted and finely tuned data sharing and facilitates health value-creating transactions with smart contracts.
Guntur Dharma Putra, Volkan Dedeoglu, Salil S. Kanhere, Raja Jurdak · 5 authors
Authorization or access control limits the actions a user may perform on a computer system, based on predetermined access control policies, thus preventing access by illegitimate actors. Access control for the Internet of Things (IoT) should be tailored to take inherent IoT network scale and device resource constraints into consideration. However, common authorization systems in IoT employ conventional schemes, which suffer from overheads and centralization. Recent research trends suggest that blockchain has the potential to tackle the issues of access control in IoT. However, proposed solutions overlook the importance of building dynamic and flexible access control mechanisms. In this paper, we design a decentralized attribute-based access control mechanism with an auxiliary Trust and Reputation System (TRS) for IoT authorization. Our system progressively quantifies the trust and reputation scores of each node in the network and incorporates the scores into the access control mechanism to achieve dynamic and flexible access control. We design our system to run on a public blockchain, but we separate the storage of sensitive information, such as user's attributes, to private sidechains for privacy preservation. We implement our solution in a public Rinkeby Ethereum test-network interconnected with a lab-scale testbed. Our evaluations consider various performance metrics to highlight the applicability of our solution for IoT contexts.
Bogahawatte W.W.M.K. A, Isuri Samanmali A.H. L, Perera K.D. M, Kavindi M.A. T · 6 authors
Cheque Truncation System (CTS) is an image-based cheque clearing framework used in Sri Lanka. This semi manual process has certain limitations and takes up to 3 working days to clear an inter-bank national cheque in Sri Lanka. Faced with the limitations of this system, cheque users and commercial banks must need an efficient and a secured system which can clear a cheque within less than 24 hours along with providing integrity and confidentiality to the system. This research portrays an automated solution, which is feasible for any commercial bank in Sri Lanka, to address above-mentioned issues. The proposed system is based on the blockchain where all banks willing to take an interest in this framework must connect the proposed blockchain based system to supply the quicker cheque clearance to its clients. Answers were proposed with a complete framework consisting of four main phases: (i) paper cheque clearing process, (ii) digital cheque issuing and clearing process, (iii) cheque fraud detection process and (iv) cheque transaction securing process. Python along with Flutter framework and Ethereum were the major technologies used for implementing the system. The proposed system is highly scalable as Ethereum provides added integrity to the system. The approach advocates the customer as well as the bank with much simpler and speedier cheque clearing process with increased security. It also contributes with a paper cheque fraud detection system with faster and reliable results. The proposed system provides benefits to the user as well as the bank by addressing the requirement of producing a secure, effective and environment friendly system. Finally, CheckMate permits a consistent stream of cheque clearance operation for the payer and the payee without any mediators.
Ch. Sanjeev Kumar Dash, Ajit Kumar Behera, Sarat Chandra Nayak, Satchidananda Dehuri
The cryptocurrency price movement behaves randomly and fluctuates like other stock markets. Prediction of cryptocurrency is a recent area of research interest and budding fast. The underlying nonlinearities in its price series make its prediction challenging. Sophisticated methodologies for accurate prediction of cryptocurrency are highly desired. Artificial neural networks (ANNs) are good approximators, however their accuracy is greatly subjective to optimal network structure and learning method. This article designs optimal ANNs for efficient cryptocurrency prediction using quasi opposition based Rao algorithms, i.e. QORA-ANN. The model explores a set of potential ANNs in the search space and lands at an optimal network through the evolving process. Historical data from four emerging cryptocurrencies such as Bitcoin, Litecoin, Ethereum, and Ripple are used to evaluate the QORA-ANN. The prediction ability of the proposed approach is compared with few similar methods such as ANN trained with genetic algorithm, differential evolution and particle swarm optimization (i.e. ANN-GA, ANN-DE, ANN-PSO), support vector machine (SVM), and multilayer perceptron (MLP). From exhaustive simulation studies and comparative result analysis it is found that the QORA-ANN method performed better than others and hence can be suggested as an efficient tool for cryptocurrencies prediction.
Faiza Loukil, Chirine Ghédira, Khouloud Boukadi, Benharkat Aïcha-Nabila
Data analytics based on the produced data from the Internet of Things (IoT) devices is expected to improve the individuals' quality of life. However, ensuring security and privacy in the IoT data aggregation process is a non-trivial task. Generally, the IoT data aggregation process is based on centralized servers. Yet, in the case of distributed approaches, it is difficult to coordinate several untrustworthy parties. Fortunately, the blockchain may provide decentralization while overcoming the trust problem. Consequently, blockchain-based IoT data aggregation may become a reasonable choice for the design of a privacy-preserving system. To this end, we propose PrivDA, a Privacy-preserving IoT Data Aggregation scheme based on the blockchain and homomorphic encryption technologies. In the proposed system, each data consumer can create a smart contract and publish both terms of service and requested IoT data. Thus, the smart contract puts together into one group potential data producers that can answer the consumer's request and chooses one aggregator, the role of which is to compute the group requested result using homomorphic computations. Therefore, group-level aggregation obfuscates IoT data, which complicates sensitive information inference from a single IoT device. Finally, we deploy the proposal on a private Ethereum blockchain and give the performance evaluation.
Philippos Gorgoris
Kurz nach der Veröffentlichung des White Papers zu Bitcoin im Jahr 2008 wurde Blockchain zu einer der am meisten diskutierten und gehypten Technologien der letzten zwei Jahrzehnte. Bitcoin führte eine kryptografisch gesicherte dezentrale Plattform für die Übertragung digitaler Vermögenswerte (die Kryptowährung Bitcoin) mit freiem Zugriff für alle ein. Einige Jahre später ging ein neuer „Player“ einen Schritt weiter: Ethereum führte die Idee eines Blockchain-basierten globalen, dezentralen Computers ein, auf dem jeder Programme auf beobachtbare und transparente Weise bereitstellen und ausführen kann. Diese als Smart Contracts (SCs) bezeichneten Programme sind zwar in der Lage, jedes entscheidbare Problem zu berechnen, sie ermöglichen jedoch in erster Linie Parteien, ein Rahmenwerk für Verträge einzurichten, ohne dass ein vertrauenswürdiger Vermittler erforderlich ist. Tatsächlich verlagert sich das Vertrauen dadurch zu den transparenten Mechanismen der Blockchain. In dieser Arbeit untersuchen wir das Ökosystem von Ethereum hinsichtlich der auf der Mainchain bereitgestellten SCs und legen einen Fokus auf die in den SCs verwendeten Authentifizierungsmuster. Diese Muster beschränken einige Funktionen der SCs, indem sie nur bestimmten Adressen erlauben, den abgesicherten Teil der Funktion auszuführen. Als Methoden für unsere Analyse führen wir die symbolische Ausführung und die Taint-Analyse ein, welche Werkzeuge sind, mit denen der Bytecode eines Programms semantisch analysiert wird. Basierend auf diesen Tools schlagen wir heuristische Erkennungsstrategien vor, um automatisch vier Authentifizierungsmuster zu erkennen, die wir im Ethereum-Bytecode von SCs finden. Darüber hinaus bewerten wir die Erkennungsstrategien anhand eines Testsatzes manuell klassifizierter SCs.
Ilya Grishchenko
The Android platform is undoubtedly the most popular platform for smartphones, with thousands of new applications becoming available daily and billions of app installations each year. Ethereum is the most popular smart contract platform, with thousands of applications on the blockchain serving as trading platforms and providing other functionalities. Due to these platforms’ popularity, security issues in their applications may reach a catastrophic scale with ease. Several prominent automated techniques help to reveal security problems in applications at the early stages of expansion. One such technique is static analysis. This thesis focuses on the design of static analysis techniques for Android apps and smart contracts distributed in the form of low-level code (bytecode).After installation, an Android app may get access to a set of sensitive information sources (e.g., location data). Unfortunately, exposure of such information to third parties has led in the past to several cases of privacy breach, and continues to be a serious threat. In this thesis, we tackle information flow propagation in the bytecode of Android applications by sound Horn-clause based abstraction techniques. This work will be the first to use Horn-clause based techniques in the context of security analysis. Moreover, we prove that our approach is sound, that is, our approach provides guarantees for its results. As a consequence, it can be used to show the absence of explicit data leaks in an app. Furthermore, Horn-clause based abstraction techniques are not limited to information propagation tasks, that is, our techniques can be used to show any kind of program property expressed as a reachability property. In addition, our Horn-clause based techniques scale to large codebases, benefit from the advancements in Satisfiability Modulo Theory solving, and allow for favorable performance with respect to the state-of-the-art. We instantiate the principles that were obtained while developing the analysis techniques for Android applications in the context of Ethereum smart contracts distributed in the form of Ethereum Virtual Machine (EVM) bytecode. Smart contracts are programs mainly used to perform financial operations (e.g., auctions) on cryptocurrency blockchains (e.g., Ethereum). Recent attacks demonstrate that certain vulnerabilities in smart contracts might cause severe money loss and an overall decrease of trust in the technology. Therefore, security analysis of EVM bytecode is in the focus of the research community. This thesis presents two results which establish the foundations for sound security analysis of EVM bytecode. First, the semantics of EVM bytecode is mechanized for the first time and tested against the official Ethereum test suite. This result facilitates both the design of analysis techniques and establishing their correctness properties. Second, this thesis provides the first sound Control Flow Graph reconstruction solution for EVM bytecode, that is, our analysis guarantees that reachable parts of the code are never pruned. This guarantee is required by a number of security properties for smart contracts. We also develop a tool implementing our analysis and successfully evaluate it on a big collection of real-world contracts.
J Rebekah, M. Preethi, K. Sandhya, K Naganandhini
cryptocurrency is a digital currency that leads the market nowadays. The knowledge about which led to the destination of cryptocurrency and the evolution of cryptocurrency is explained. Bitcoins and Ethereum are the most popular cryptocurrencies. They use blockchain technology. Thereby we see the future of cryptocurrency.
He Wang, Hu Zheng
Abstract The block chain technology enjoys a promising development prospect. As one of the most popular technologies, block chain has been heatedly studied and researched by people from all walks of life. Based on an introduction to the technical background and basic concepts of block chain, by analyzing the technical architecture and working principle of block chain, this paper systematically explains the key technologies of block chain, namely decentralization, proof of work (POW), smart contract and Ethereum, and further discusses the development of the block chain technology, 5G, the Internet of Things and the future wireless network.
Ming‐Tuo Zhou, Feng-Guo Shen, Tian-Feng Ren, Xinyu Feng
Cloud computing has been widely used in the field of information services. However, large-scale Internet of things (IoT) applications are raising new challenges to cloud computing architecture. Edge computing, which complements cloud computing, is considered to be the way to address these challenges. Volunteer computing, which harvests idle resources in the network can improve the hardware utilization rate and support tens of billions of IoT devices. In view of the limitations of traditional volunteer computing that cannot provide realtime services and has no mechanism to reward services in existing volunteer clouds, this paper presents blockchain-based volunteer edge cloud. A common runtime environment is provided by container technology, and blockchain smart contract is used for critical business steps and computing service payment. Volunteer edge cloud systems based on blockchain is introduced from a top-level perspective, and a prototype system build on Ethereum and KubeEdge is described in detail. On top of the prototype system, we deployed an example IoT application of robot formation control. It demonstrates the benefits of volunteer edge cloud in reducing the complexity of IoT devices, improving the flexibility of software development, and paying the computing service.
Lodovico Giaretta, Ioannis Savvidis, Thomas Marchioro, Šarūnas Girdzijauskas · 7 authors
We envision PDS<sup>2</sup>, a decentralized data marketplace in which consumers submit their tasks to be run within the platform, on the data of willing providers. The goal of PDS2is to ensure that users maintain full control on their data and do not compromise their privacy, while being rewarded for the value that their data generates. In order to achieve this, our marketplace architecture employs blockchain technology, privacy-preserving computation and decentralized machine learning. We then compare different potential solutions and identify the Ethereum blockchain, trusted execution environments and gossip learning as the most suitable for the implementation of PDS<sup>2</sup>. We also discuss the main open challenges that are left to tackle and possible directions for future work.
Emanuele Viglianisi, Mariano Ceccato, Paolo Tonella
The peculiar novelty of smart contracts is a computational model where irreversible transactions are stored in a distributed persistent data storage, namely the blockchain. The technical nature of this new type of software opens to new kinds of faults, which require specific test capabilities to be revealed. In this paper we present SOCRATES, an extensible and modular framework to automatically test smart contracts. The distinctive features of SOCRATES are: (1) a collection of composable behaviours that exercise smart contracts in the blockchain; (2) it deploys a society of bots, with the purpose of detecting defects arising from multi-user interactions, which are impossible to reveal when deploying a single bot. Our empirical investigation demonstrates that SOCRATES is able expose both known and previously unknown faults in smart contracts that are actively run in the official Ethereum blockchain. Moreover, we show that a society of multiple bots is more efficient in fault exposure than a single bot alone.
Anis Jarboui, Emna Mnif
Purpose After the COVID-19 outbreak, the Federal Reserve has undertaken several monetary policies to alleviate the pandemic consequences on the markets. This paper aims to evaluate the effects of the Federal Reserve monetary policy on the cryptocurrency dynamics during the COVID19 pandemic. Design/methodology/approach We examine the response and feedback effects via an event study methodology. For this purpose, abnormal returns (AR) and cumulative abnormal returns (CARs) around the first FOMC (Federal Open Market Committee) announcement related to the COVID-19 pandemic for the top five cryptocurrencies are explored. We, further investigate the effect of the eight FOMC statement announcements during the COVID19 pandemic on these cryptocurrencies (Bitcoin, Ethereum, Tether, Litecoin, and Ripple). In the above-mentioned crypto-currency markets, we investigate the presence of bubbles by using the PSY test. We then examine the concordance of the dates of these bubbles with the dates of the FOMC announcements. Findings The empirical results show that the first FOMC event has a negative significant effect after 4 days of the announcement date for all studied cryptocurrencies except Tether. The results also indicate that cumulative abnormal returns are significant during the event windows of (−3,8), (−3,9), and (−3,10). Besides, we find that Bitcoin, Ethereum and, Litecoin lived short bubbles lasting for a few days. However, Ripple and Tether markets present no bubbles and no explosive periods. Research limitations/implications This paper presents trained proof that FOMC announcements have a positive effect on volatility's predictive capacity. This work therefore promotes the study of the data quality of volatility in future research as well. Practical implications The justified effect of the FOMC announcements on cryptocurrency as a speculative asset has practical implications for investors in building their trading strategies in anticipation of the next FOMC announcement. Therefore, this study implies that the FOMC announcements contain very relevant information for investors in the cryptocurrency market. This research may not only encourage a better understanding of the evolution of the expectations of policymakers, but also facilitate a better understanding of how these expectations are developed. Originality/value The COVID-19 pandemic has disturbed the stability of financial markets, inciting the Fed to take some monetary regulations. To the best of our knowledge, this study is the first one that analyses the response of five major cryptocurrencies to FOMC announcements during COVID 19 pandemic and associates these dates with bubble occurrences.
Marlene Kuhn, Felix Funk, Guanlai Zhang, Jörg Franke
No abstract is available for this record.
Elva Leka, Besnik Selimi
Academic degrees are subject to corruptions, system flaws, forgeries, and imitations. In this paper we propose to develop a blockchain smart contract-based application using Ethereum Platform, to store, distribute and verify academic certificates. It constitutes a trusted, decentralized certificate’s management system that can offer a unified viewpoint for students, academic institutions, as well as for other potential stakeholders such as employers. The article describes the implementation of three main parts of our proposed solution that includes: verification application, university interface and accreditor interface. This application avoids administrative barriers, makes the process of deployment, verification, and validation of certificates faster, efficient, and more secure. Additionally, it offers confidentiality of the data by using AES encryption algorithm before creating transactions and allows bulk submission of multiple academic certificates.
Yannan Li, Yong Yu, Willy Susilo, Zhiyong Hong · 5 authors
5G and beyond (B5G) networks are leading a digital revolution in telecommunication in both academia and industry. It brings new paradigms in many aspects of people's daily lives due to its advantages. However, it still leaves some issues in terms of security and privacy as challenges. Blockchain, the public database, is an alternative to the traditional centralized systems, serving as the backbone technique in many systems, including manufacturing, economics, and industry. Blockchain is promising in solving the security issues in the sense that it provides desirable properties including decentralization, transparency, immutability, and so on. In this article, we investigate typical security and privacy issues in edge intelligence in B5G networks and devise a framework to integrate blockchain with such systems, which can provide guaranteed security as well as privacy. We also illustrate several possible solutions to these security and privacy issues in edge intelligence in B5G systems based on blockchain and Ethereum to show how blockchain contributes to the coming B5G networks.
Komal Kalra
Financial Regulation is a form of compliance system that subjects financial institutions to certain requirements and restrictions. Investment Compliance is an example that involves investment restrictions and monitoring on behalf of investors. Hedge Funds differ from other traditional funds such as mutual funds because of their ability to employ complex investment and hedging techniques. These are private entities with few public disclosure requirements. This is useful in a way as the strategies used are confidential which allows financial agents to participate in the financial markets without any fear of information leakage, hence promoting liquidity. However, this is often implied as a lack of transparency. Hedge Funds are expected to produce higher returns, but sometimes investors seek a risk guarantee in addition to higher returns. However, too much transparency rules out the incentives financial entities have by participating in the first place. On the other hand, too much secrecy may give rise to malicious entities that can break the rules due to a lack of compliance. We aim to solve this problem of protecting investors while ensuring the privacy of financial bodies using zero knowledge proofs. Proofs can be visualized as a way of providing enough information to investors while the zero-knowledge property of proofs maintains the privacy of the fund manager’s strategies. We propose a protocol to address this scenario using Zokrates, a framework for verifiable computation using Zk-SNARKs on Ethereum, to encode the constraints and export the verifier. Based on our implementation and analysis, it can be concluded that zero knowledge proofs provide us with a variety of ways to develop compliance systems.
Ce Zhang, Cheng Xu, Haixin Wang, Jianliang Xu · 5 authors
Blockchain has emerged as a promising solution for secure data storage and retrieval for decentralized applications. To scale blockchain systems, a prevailing approach is to employ a hybrid storage model, where only small meta-data are stored on-chain while the raw data are outsourced to an off-chain storage service provider. The key issue for query processing in such a system is the design of gas-efficient authenticated data structure (ADS) to authenticate the query results. In this paper, we study novel ADS schemes for authenticated keyword search in hybrid-storage blockchains. We first propose the Suppressed Merkle inverted (Merkleinv) index, which maintains only a partial ADS structure on-chain that can be securely updated with a logarithm-sized cryptographic proof. Moreover, we propose a Chameleon inverted (Chameleoninv) index that leverages the chameleon vector commitment to achieve a constant maintenance cost. It is further optimized with Bloom filters to enhance the query and verification performance. We prove the security of the proposed ADS schemes and evaluate their performance using real datasets on the Ethereum platform. Experimental results show that, compared to a baseline solution, the proposed Merkleinvand Chameleoninvindexes reduce the average on-chain maintenance cost from US$10.39 down to US$2.50 and US$0.24, respectively, without sacrificing much the query performance.
Riaz Ahmad Ziar, Syed Irfanullah, Wajid Ullah Khan, Abdus Salam
Blockchain technology provides several suitable characteristics such as immutability, decentralization and verifiable ledger. It records the transactions in a decentralized way and can be integrated into several fields like eHealth, e-Government and smart cities etc. However, blockchain has several privacy and security issues, one of them is the on-chain data privacy. To deal with this issue we provide a privacy-preserving solution for permission less blockchain to empower the user to take control of transaction data in the open ledger. This work focuses on designing and developing the peer-to-peer system using symmetric cryptography and ethereum smart contract. In this scheme, we create smart contracts for the interaction of the data provider, data consumer, and access control list. Data providers register authorized users in the access control list. Data consumers can check their validity in the access control list. After successful validation, data consumers can request the security key from data providers to access secret information. Based on successful validation, a smart contract that is created between the data provider and data consumer is executed to send a key to the data consumer for accessing the secret information. The smart contracts of this proposed model are modeled in solidity, and the performance of the contracts is assessed in the Ropsten test network.
Jie Xiang, Zhemin Yang, Shunfan Zhou, Yang Min
No abstract is available for this record.
Ahmed Jeribi, Yasmine Snene Manzli, Islem Khefacha
Abstract Using the DCC-GARCH (1.1) model, we investigate the dynamic conditional correlations between Tunisian indices, digital assets, and gold prices for the period ranging from 4 January 2016 to 30 April 2020. Our findings reveal that digital assets (Bitcoin, Ripple, Ethereum, and Dash) and gold can be considered as hedge and diversifier assets before the 2020 global pandemic. Contrarily to Ripple which can be a safe haven asset for the Tunisian investors in early 2020, Monero can be considered as a diversifier asset more than a hedge. Finally, our results can be useful to Tunisian investors when accounting for implementing hedging strategies. JEL classification: C22, C5, G1