Jongyeop Kim, Hayden Wimmer, Hong Liu, Seong-Soo Kim
Big data analysis for accurate predictions requires adherence to systematic procedures. This study shows an entire data analysis phase from the data collection to model evaluation using the Long Short-Term memory(LSTM) for cryptocurrency price prediction. Three different coin prices are directly collected from the CoinMarketCap in nearly real-time by applying the web scraping technique. The LSTM model trained with this data varying random seed or static seed parameters to find optimal conditions, leading to better accuracy of the LSTM model. Our model evaluated their accuracy in terms of MAE, RMSE, and SMAPE indicators. As a result of this experiment, most of the best candidate parameters are classified at the fixed seed trail in terms of the RMSE for Bit coin, Ethereum, and Lite Coin.
Jongyeop Kim, Seong-Soo Kim, Hayden Wimmer, Hong Liu
This study aims to predict cryptocurrency prices using Long Short-Term Memory(LSTM) and Gated Recurrent Unit(GRU) for three different coins: BitCoin, Ethereum, and Litecoin. For the training data for prediction, two data sets with different statistical characteristics in terms of Kurtosis and Skewness are used. LSTM and GRU models are trained and tested on the same hyperparameter configuration while increasing the number of epochs from 1 to 30. The accuracy of each model is measured by Root Mean Square Error (RMSE) and MAE (Mean Absolute Error). As a result of comparing GRU and LSTM, in BTC and ETH, the GRU was more advantageous for the downward stabilization trend, and the LSTM was suitable for the upward stabilization trend. However, in case of low-priced LTC, LSTM and GRU showed the same performance in sample type A, and in the case of type B, GRU was more accurate.
Walid Mensi, Mobeen Ur Rehman, Muhammad Shafiullah, Khamis Hamed AlâYahyaee ¡ 5 authors
This paper examines the high frequency multiscale relationships and nonlinear multiscale causality between Bitcoin, Ethereum, Monero, Dash, Ripple, and Litecoin. We apply nonlinear Granger causality and rolling window wavelet correlation (RWCC) to 15 min-data. Empirical RWCC results indicate mostly positive co-movements and long-term memory between the cryptocurrencies, especially between Bitcoin, Ethereum, and Monero. The nonlinear Granger causality tests reveal dual causation between most of the cryptocurrency pairs. We advance evidence to improve portfolio risk assessment, and hedging strategies.
Medical Records (MR) consisting of Personal Health Record (PHR), Electronic Health Record (EHR), dan Electronic Medical Record (EMR). Electronic Health Record (EHR) is a medical record that can be accessed and have certain limitations. The challenge in implementing MR is how to be able to collect, store, and analyze patient data in a comprehensive and integrated manner without having to violate patient privacy. The implementation of MR is how to transmit data between hospitals. To solve the problems and issues faced in implementing MR, there is a technology that can overcome this, one of which is using blockchain technology. Blockchain is a distributed ledger that managed by many participants in an availability manner. Ethereum is a blockchain platform that anyone can use to create and deploy decentralized applications that run on the blockchain network. The data stored on the Ethereum blockchain will always be there and can be seen as long as the blockchain network is still online. With ethereum, the process of sharing data will be easy to do using a computer belonging to the hospital as a blockchain node. The result of implementing blockchain into medical record is now the data can be shared securely between hospitals.
E-Voting system generally adopts the client-server architecture where the server is the responsible entity of all data in the system. Such a system poses several issues regarding information security such as data integrity of the election result, the confidentiality of voter identity with its vote and the auditability of transactions. This research presents an implementation of blockchain-based Ethereum on the E-Voting system to protect the information security with a distributed storage. The e-Voting system is implemented with three main components: private blockchain network, smart contract, and web service as an interface to manager and voters. The functional evaluation on the data store, display, update, delete, verify voters, authenticate voters, and the integrity of the election process in the private blockchain network are all well-functioning, even without an overvote. The nonfunctional evaluation shows that the system can guarantee the data integrity of the election result, the confidentiality of voter identity with its selection, the auditability of transactions, and the maximum scale of load that system can handle. Based on these results, E-Voting system with a blockchain-based Ethereum give a better alternative than those implemented with a client-server architecture.
In this technical era which changes every second, Blockchain plays an advanced role by extending its application in several areas such as telecommunication, networking, and mobile applications, so, now blockchain technology as a decentralized application is made an efficient, immutable, and secured platform to economical society in many aspects specially for database analysis and networking purposes. Recently, many organizations all around the world are using this technology to meet with the competitive business society because they understand the potential of this decentralized management platform. Although there are many systems existing and developing for bracing the bond between organization and customers, there is a lack of systems for employee evaluation. Decentralized Ethereum private blockchain network which this paper has described will enable company generated token transactions among the employees in the organization. The system allows an employee to reward a number of tokens to his subordinates on their performance base.
Mirza Jabbar Aziz Baig, M. Tariq Iqbal, Mohsin Jamil, Jahangir Khan
An open-source P2P energy trading platform facilitates energy trading amongst the peers. The proposed system provides real time data acquisition, monitoring and control of self-generated energy at a remote location. The trading activities are done on a web interface that uses a private Ethereum blockchain. A smart contract is deployed on the Ethereum blockchain and the trading activities performed on the web interface are recorded on a tamper-proof blockchain network. An internet of things platform is used to monitor and control the self-generated energy. Energy data is collected and processed by means of ESP32-S2 microcontrollers using field instrumentation devices which are connected to the voltage source and load. An open-source decentralized Peer-to-Peer (P2P) energy trading system, designed on the blockchain and internet of things (IoT) architecture is proposed. The hardware setup includes a relay, a current sensor, a voltage sensor, a Wi-Fi router and ESP32-S2 microcontroller. For data transfer the Message Queuing Telemetry Transport (MQTT) protocol is used over a local network. ESP32-S2 is set up as MQTT client and Node-Red IoT server is used as MQTT broker. Hypertext Transfer Protocol (http) request method is implemented to connect the Node-Red server with the web interface developed using React.JS library. The system design, implementation, testing, and results are presented in this paper.
Simón Fernåndez-Våzquez, Rafael Rosillo, Luis Meijueiro, Raul Alonso Alvarez ¡ 5 authors
Blockchain is increasingly gaining interest in both the academic and professional worlds. The implementation of this decentralised and distributed network has started taking place, firstly in the financial world and in recent years reaching to other industries. Nevertheless, not all blockchain networks are the same, and choosing the right consensus algorithm is important for companies willing to invest in this technology. Companies eager to implement blockchain should understand the underlying architecture when selecting a particular network. Through an in-depth analysis, this paper aims to explore and compare from a technical perspective the three biggest permissionless blockchain networks by market capitalisation: Bitcoin, Ethereum and Ripple. Our research shows that Bitcoin gains a competitive advantage as a widely adopted means of payment, Ethereum excels in adopting a robust and flexible smart contract functionality whilst Ripple is most suitable for cross-border payments due to its scalability and fast processing speed. Based on the comprehensive analysis of the networks and their consensus protocols, this paper is designed to set the ground for further studies on the emerging applications of blockchain in numerous sectors.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
A smart contract is a digital protocol (software code) that enables automated monitoring and executing contractâs provisions without the need for intermediaries. Blockchain technology allows implementing smart contracts through a distributed ledger, but has no reliable way of enforcing legal rules. For example, in networks such as Bitcoin, it is possible to engage in illegal activities such as money laundering and dealing in weapons. In addition, it is impossible to enforce and audit legal costs such as taxes and duties. This research has devised a plan that allows official institutions to enforce the rules and audits efficiently during automatic execution process of smart contracts. This article discusses five important challenges in applying legal rules to Blockchain: the accreditation to the contracting partiesâ and the goodsâ nature, collecting legal costs, enforcing territorial laws and auditing. We present âHyper Smart Contractâ, a method for regulating Blockchain-based smart contracts and assess the limitations of the current generation of smart contracts on Ethereum to ensure a proper implementation of this plan. The performance of proposed method evaluated on a motivation application.
Sep 9, 2021¡(2021, August). Application of Blockchain Technology for Educational Platform. In International Conference on Human Interaction and Emerging Technologies (pp. 1283-1287). Springer, Cham
Matija Ĺ ipek, Martin Ĺ˝agar, Branko MihaljeviÄ, Nikola DraĹĄkoviÄ
Nowadays, huge amounts of data are generated every second, and a quantity of that data can be defined as sensitive. Blockchain technology has private, secure, transparent and decentralized exchange of data as native. It is adaptable and can be used in a wide range of Internet-based interactive systems in academic and industrial settings. The essential part of programmable distributed ledgers such as Ethereum, Polkadot, Cardano and other Web 3.0 technologies are smart contracts. Smart contracts are programs executed on the global blockchain, the code is public as well as all of the data managed within the transactions, thus creating a system that is reliable and cannot be cheated if designed properly. In this paper, in order to make the educational system more transparent and versatile we will describe an educational learning platform designed as a distributed system.
Timothy Tzen Vun Yap, Ting Fong Ho, Hu Ng, Vik Tor Goh
<ns3:p> <ns3:bold>Background:</ns3:bold> This research uses exploratory graph analysis to analyze the transaction data of the Ethereum network. This is achieved through network visualization and mathematical and statistical modelling of the network data. </ns3:p> <ns3:p> <ns3:bold>Methods:</ns3:bold> The dataset used in this study was extracted from the Ethereum in the BigQuery public dataset, specifically selected transactions in July 2019. The transactions were firstly modelled as network graphs and then visualized using the Kamada-Kawai and force-directed graphs layouts. Further modelling was explored with classical random graph and network block, with emphasis on network cohesion, hierarchical clustering and community membership. </ns3:p> <ns3:p> <ns3:bold>Results:</ns3:bold> Looking at the network visualization and hierarchical clustering of the data, the network shows 170 clusters, the largest having 135 members. Through random graph modelling the optimum number of clusters is shown to be 95. Referring to the generated dendrograms, notable large transactions center around the DRINK token, the Maximine Exchange, the Upbit2 Exchange and the IDEX Exchange, identified through public disclosure of their Ethereum addresses. The network graphs tend to go towards the DRINK smart contract and the Maximine Exchange, indicating deposit actions, while it is the opposite for the IDEX Exchange. Further analysis also shows a different number of communities than the expected number. Falling short of the expected 170 clusters, the model is not able to capture additional mechanism that may be present at the density and social interaction distribution level of the network. On the other hand, network block modelling shows only four major clusters out of the 170 expected clusters, an indication that the model is not able to capture the network sufficiently. </ns3:p> <ns3:p> <ns3:bold>Conclusions:</ns3:bold> The study was able to capture and model the interconnectedness of the system with its notion of elements, in this case, the transactions on the network. </ns3:p>
Kushal Babel, Philip Daian, Mahimna Kelkar, Ari Juels
We introduce the Clockwork Finance Framework (CFF), a general purpose, formal verification framework for mechanized reasoning about the economic security properties of composed decentralized-finance (DeFi) smart contracts. CFF features three key properties. It is contract complete, meaning that it can model any smart contract platform and all its contracts--Turing complete or otherwise. It does so with asymptotically constant model overhead. It is also attack-exhaustive by construction, meaning that it can automatically and mechanically extract all possible economic attacks on users' cryptocurrency across modeled contracts. Thanks to these properties, CFF can support multiple goals: economic security analysis of contracts by developers, analysis of DeFi trading risks by users, fees UX, and optimization of arbitrage opportunities by bots or miners. Because CFF offers composability, it can support these goals with reasoning over any desired set of potentially interacting smart contract models. We instantiate CFF as an executable model for Ethereum contracts that incorporates a state-of-the-art deductive verifier. Building on previous work, we introduce extractable value (EV), a new formal notion of economic security in composed DeFi contracts that is both a basis for CFF and of general interest. We construct modular, human-readable, composable CFF models of four popular, deployed DeFi protocols in Ethereum: Uniswap, Uniswap V2, Sushiswap, and MakerDAO, representing a combined 24 billion USD in value as of March 2022. We use these models along with some other common models such as flash loans, airdrops and voting to show experimentally that CFF is practical and can drive useful, data-based EV-based insights from real world transaction activity. Without any explicitly programmed attack strategies, CFF uncovers on average an expected $56 million of EV per month in the recent past.
Background: Academic literature on blockchains has focused on Bitcoin, which is traditionally associated with right-wing libertarianism. This article looks at Ethereum, an alternative that emerged in Canada and is now the second most used blockchain technology after Bitcoin. Analysis: Using participatory observation supplemented with publicly available material, this article examines the ideologies and imaginaries surrounding Ethereum and how they are articulated with its technical design. Conclusion and implications: Ethereumâs design ostensibly widens the ideological spectrum of cryptocurrency while âmaskingâ certain currency ideologies still prominent within it. This complicates the distinction seen in the literature between blockchain as currency and blockchain as media and points to the increasing need to study non-currency-based blockchain technologies.
Hye-Yeong Shin, Meryam Essaid, Sejin Park, Hongtaek Ju
Bitcoin is the most representative UTXO-based blockchain platform, and many studies have been conducted related to it. However, account-based blockchains such as Ethereum are not yet profoundly analyzed. There is an urgent need to track all cryptocurrency transactions involved with illegal activities to deanonymize and identify malicious users. To link users' accounts to real identities in both networks, we first need to examine the differences between Ethereum and Bitcoin to propose an efficient deanonymizing method. Therefore, this paper compares and analyzes the wallet address clustering method of Bitcoin and Ethereum.
Selma Steinhoff, Chrysoula Stathakopoulou, Matej PavloviÄ, Marko VukoliÄ
Reconfiguration of long-lived blockchain and Byzantine fault-tolerant (BFT) systems poses fundamental security challenges. In case of state-of-the-art Proof-of-Stake (PoS) blockchains, stake reconfiguration enables so-called long-range attacks, which can lead to forks. Similarly, permissioned blockchain systems, typically based on BFT, reconfigure internally, which makes them susceptible to a similar "I still work here" attack. In this work, we propose BMS (Blockchain/BFT Membership Service) offering a secure and dynamic reconfiguration service for BFT and blockchain systems, preventing long-range and similar attacks. In particular: (1) we propose a root BMS for permissioned blockchains, implemented as an Ethereum smart contract and evaluate it reconfiguring the recently proposed Mir-BFT protocol, (2) we discuss how our BMS extends to PoS blockchains and how it can reduce PoS stake unbonding time from weeks/months to the order of minutes, and (3) we discuss possible extensions of BMS to hierarchical deployments as well as to multiple root BMSs.
Soo Hoon Maeng, Meryam Essaid, Sejin Park, Hongtaek Ju
The Ethereum network uses Kademlia, a well-known P2P network, which allows the search for new nodes, and the change of connection with neighboring nodes. The Ethereum network must cope with security attacks such as DDoS attacks, 51% attacks, and Sybil attacks, and scalability issues, which slows down the transaction processing speed per second (TPS) as the network expands. A deep analysis of the dynamically changing topology and the connection between the nodes constituting the topology is needed to solve these problems. Therefore, in this paper, we measure the topology in the Ethereum network using a passive probing data collection to search for active nodes in the network and an active probing method to check the activity of nodes participating in the Ethereum network. Our results give a clear insight into the topology properties and topology visualization.