In this paper, we investigated the evolution of the External owned account Trading Network(ETN) on Ethereum from August 10th, 2015 to June 9th, 2017 through the perspective of network science. It is showed that the evolution of the topological properties of the ETN and important events are closely related. The average degree of the ETN is not constant but fluctuates within a small range of (2.1, 3.2). And there exists the extremely strongly positive correlation between the number of nodes and the number of edges in the ETN. Moreover, following the events happening, the degree distribution of ETN changes obviously. Moreover, the ETN has smaller values of degree correlation coefficient and clustering coefficient than that of the randomized graph with the same degree sequence, which implies that ETN shows the disassortative mixing pattern by degree and owns few triangles. Through the method of k-shell decomposition, our investigation shows the core of the ETN grows stepwise.
Summary The “last mile” problem in logistics is challenging due to its low efficiency and high cost. To address this problem, Unmanned Aerial Vehicle (UAV) delivery such as drone delivery has been proposed and widely accepted as a promising solution. However, currently most of the existing UAV delivery systems are based on Cloud Computing which cannot efficiently meet the requirements of many real‐time services in UAV delivery systems. Meanwhile, the security issues in UAV delivery systems also raise critical concerns due to the existence of multiple participants (such as the sender, middler, and receiver) who may not maintain a mutual trust relationship among them. How to secure the UAV delivery process in such an untrusted environment is still a challenging issue. In this paper, we propose a Mobile Edge Computing (MEC) and blockchain‐based UAV delivery system to resolve the “last mile” problem in logistics. Specifically, based on the MEC architecture, the blockchain nodes are deployed on the edge nodes to facilitate and secure the UAV delivery process. To verify the effectiveness of our proposed solution, a MEC‐based UAV delivery system prototype with a private blockchain on the Ethereum platform is implemented. Through the security analysis and performance evaluation, it is proven that our proposed solution can effectively solve the “last mile” problem and address the security issues in UAV delivery systems.
This study will investigate the predictability of a Chaotic time-series data using Reservoir computing (Echo State Network), Deep-Learning(LSTM) and Machine- Learning(Linear, Bayesian, ElasticNetCV , Random Forest, XGBoost Regression and a machine learning Neural Network) on the short (1-day out prediction), medium (5-day out prediction) and long-term (30-day out prediction) pricing of Bitcoin and Ethereum Using a range of machine learning tools, to perform feature selection by permutation importance to select technical indicators on the individual cryptocurrencies, to ensure the datasets are the best for predictions per cryptocurrency while reducing noise within the models. The predictability of these two chaotic time-series is then compared to evaluate the models to find the best fit model. The models are fine-tuned, with hyperparameters, design of the network within the LSTM and the reservoir size within the Echo State Network being adjusted to improve accuracy and speed. This research highlights the effect of the trends within the cryptocurrency and its effect on predictive models, these models will then be optimized with hyperparameter tuning, and be evaluated to compare the models across the two currencies. It is found that the datasets for each cryptocurrency are different, due to the different permutation importance, which does not affect the overall predictability of the models with the short and medium-term predictions having the same models being the top performers. This research confirms that the chaotic data although can have positive results for shortand medium-term prediction, for long-term prediction, technical analysis basedprediction is not sufficient.
The production of counterfeit money has a long history. It refers to the creation of imitation currency that is produced without the legal sanction of government. With the growth of the cryptocurrency ecosystem, there is expanding evidence that counterfeit cryptocurrency has also appeared. In this paper, we empirically explore the presence of counterfeit cryptocurrencies on Ethereum and measure their impact. By analyzing over 190K ERC-20 tokens (or cryptocurrencies) on Ethereum, we have identified $2,117$ counterfeit tokens that target 94 of the 100 most popular cryptocurrencies. We perform an end-to-end characterization of the counterfeit token ecosystem, including their popularity, creators and holders, fraudulent behaviors and advertising channels. Through this, we have identified two types of scams related to counterfeit tokens and devised techniques to identify such scams. We observe that over 7,104 victims were deceived in these scams, and the overall financial loss sums to a minimum of \$ 17 million (74,271.7 ETH). Our findings demonstrate the urgency to identify counterfeit cryptocurrencies and mitigate this threat.
Abstract This study aims to explain price movements in the two largest cryptocurrencies that represent the majority of cryptocurrency market capitalization—Bitcoin and Ethereum. A VAR‐GARCH‐BEKK model is estimated to analyze how Google search interest, number of tweets and active addresses on the blockchain impact prices of Bitcoin and Ethereum over time. We find solid evidence that the amount of active addresses is the most significant variable among others influencing price movements in Bitcoin and Ethereum. Based on spillover effects and GIRFs, Google searches and tweets, to a certain extent, have impacts on the Bitcoin and Ethereum prices, but the impacts are weaker than that of active addresses in terms of magnitude and significance.
Blockchain has been used in several industries, especially in the financial area. In the game industry, blockchain has not been utilized much even with a large number of users who deserve to own their game data. There were attempts to allow players to own their in-game objects or data. But they were mostly crowdfunding platforms which were not yet in operation. In addition, users were required to use their ecosystem. In this paper, we propose a generic game architecture, using blockchain, that allows players to own their “spent time” in a game. The value of this spent time can be passed on to new games as ERC20 token on the Ethereum network and redeemed in such games. Our architecture can be used with any public blockchain. It can benefit many roles such as player, blockchain node, and game developer. Our experiment shows that the proposed architecture can be accepted by players, but other factors such as the type of gameplay and how the spent time is exchanged in a game can greatly affect the player acceptance.
The purpose of this research is to develop a job training document storage system based on the public blockchain platform. The use of public platforms is used to secure certificate data making it difficult to falsify. The use of smart contracts is used to form data that will be used in blocks to be sent to the Ethereum blockchain network. The InterPlanetary File System (IPFS) is used to store certificate files in a distributed environment so that access is easy and safe to do. The results showed that certificate data can be stored in public blockchain Ethereum infrastructure and its supporting files stored in the IPFS environment. This means that certificate data is more secure from counterfeiting because it is stored in a distributed and transparent blockchain environment.
Giuseppe Antonio Pierro, Roberto Tonelli, Michele Marchesi
Many empirical software engineering studies show that there is a great need for repositories where source code is acquired, filtered and classified. During the last few years, Ethereum block explorer services have emerged as a popular project to explore and search Ethereum blockchain data such as transactions, addresses, tokens, smart-contracts' source code, prices and other activities taking place on the Ethereum blockchain. Despite the availability of this kind of services, retrieving specific information useful to empirical software engineering studies, such as the study of smart-contracts' software metrics might require many sub-tasks, such as searching specific transactions in a block, parsing files in HTML format and filtering the smart-contracts to remove duplicated code or unused smart-contracts. In this paper we afford this problem creating Smart Corpus', a Corpus of Smart Contracts in an organized reasoned and up to date repository where Solidity source code and other metadata about Ethereum smart contracts can easily and systematically be retrieved. We present the Smart Corpus' design and its initial implementation and we show how the data-set of smart contracts' source code in a variety of programming languages can be queried and processed, get useful information on smart contracts and their software metrics. The Smart Corpus aims to create a smart-contracts' repository where smart contracts data (source code, ABI and byte-code) are freely and immediately available and also classified based on the main software metrics identified in the scientific literature. Smart-contracts source code has been validated by EtherScan and each contract comes with its own associated software metrics as computed by the freely available software PASO. Moreover, Smart Corpus can be easily extended, as the number of new smart-contracts increases day by day.
Richard Richard, Mahenda Metta Surya, Avenia Clarissa Wibowo
Artificial Intelligence (AI) and blockchain are two emerging concepts that explored exponentially in recent years. In software development, artificial Intelligence offers a sophisticated enhancement on the programming logic, while blockchain technology provides transparency and relief the obligation to trust in a central party. Both are two different technologies but considered a disruptive technology in recent years. Artificial Intelligence faces several issues related to the validity of data, algorithms, and policies, while blockchain is called so “friendly” with transparency, trust, and immutability. Both technologies are still in the early stages of their development age. Always, the opportunity for both technologies to converge in some ways would be an exciting area to be explored. This research elaborates on the technical possibilities of application development on the blockchain platform that communicate with AI to do prediction task. Oracle contract allows the data inside Ethereum blockchain to interact with the external data source.
Blockchain technology has proven to be secured and reliable technology by bringing security, trust and data integrity to distributed systems. It brought a new paradigm that helps in the existence of the cryptocurrency and eliminating the third party in a financial transaction. It has the potential of optimising, enhancing streamlining many processes outside the cryptocurrency and financial sector but the adoption of the technology is limited by the hindering performance issues. These issues are mostly around the Proof-of-Work (PoW) consensus protocol that is used by Bitcoin and Ethereum and referred to as the most secured and decentralised protocol thus, the most reliable. Unfortunately, the protocol suffers a performance degrade with the increasing size and number of transactions because of its complexity. Many industries, researchers and organisation have been working on addressing these issues but most of the attempts result in facing another issue referred to as the scalability issue; having to trade off one of security or decentralisation to get speed. Other solution such as Bitcoin lighting network improved the transaction throughput of the Bitcoin without technically addressing the issue on the blockchain, therefore, didn't face the scalability issue. This paper presents a research work of a novel approach that propose using machine learning techniques to improve the performance by enhancing the mining efficiency of the protocol. It uses the Ethereum network as a case study. The paper also aims to compare the predictive accuracy and speed of some machine learning regression models against the traditional mining method starting from the Linear regression. The objective is to determine whether using machine learning in the mining process offers a faster way of achieving consensus, therefore improving performance by reducing the time and energy consumption of the protocol without sacrificing security or decentralisation. The proposed model results in improved accuracy and faster consensus from the early experiments.
Continuous efforts are being made daily by organizations to develop special tools that can support the collection and organization of available information in order to prevent the spread of fake news. Nowadays, misinformation has been deemed as a great challenge especially with the raise of social media networks that are used as platforms for disseminating information in a digital form. This paper presents the implementation of a decentralized application deployed on the Ethereum blockchain, to be used as a tool for combating fake news and misinformation. The develop framework is proposed as a solution for publishing reliable news sources and enabling readers to self-verify the trustworthiness of the published source. An experimental scenario has been implemented that presents the effectiveness of the proposed framework.
Koushik Bhargav Muthe, Khushboo Sharma, Karthik Epperla Nagendra Sri
The market value of the Gaming industry was said to be over 138 Billion USD in 2019. Competitive Gaming or eSports was already included in the Asian Games 2020, and the Olympic committee is considering including eSports into Olympics 2024. The online gaming segment amounts up to 7 quintillion bytes of internet traffic every month. Most of this data is controlled by centralized gatekeepers like cloud agencies and game creators. This is causing many issues ranging from privacy concerns to latency. The game makers have complete rights over the game to arbitrarily change the rules, set prices for the assets, and control over game servers. Even the reward mechanisms in most of the games, including eSports, are controlled by the game producers, and these rewards have no real-world value. The motivation behind this research is to create a decentralized computation and token management infrastructure for game networks. This paper focuses on using Ethereum Blockchain, IPFS and ERC - Ethereum Request for Comment 1155 architecture to build a gaming-oriented public decentralized network.
Received wisdom portrays digital records as guaranteeing perpetuity; as the New York Times wrote a decade ago: "the web means the end of forgetting". The reality however is that digital records suffer similar risks of access loss as the analogue versions they replace. Often this risk is outsourced to specialised third parties. Common use cases include Personal Information Management (PIM): e.g. calendars, diaries, tasks, etc. Frequently these are outsourced at two removes - firstly by the individual to their employer (e.g. using a company system) and then by their employer to an external provider. So enters a new risk: organisational change; by the time the information is required the organisational chain that links user to data may be broken: the employer transitions to a different provider, the employee leaves the company, the IS provider pivots to new offerings. The advent of Distributed Ledger Technology (DLT) could help mitigate these risks; and has led to a re-evaluation of the relationship between data creation and ownership. Although DLT is an imprecise term, it typically involves data storage across organisationally separate entities in a cryptographically secure form; and therefore could present a partial solution to the risk. This project presents the first research that applies DLT to the field of PIM, furthering design science state of the art by a novel implementation of a calendar application on the Ethereum blockchain. It also extends current research in utilising DLT in digital preservation, namely by enacting a continuum approach within a DL that allows for transfer of ownership of digital objects as they transition from individual to collective relevance. Finally it provides guidelines for future use of DLT within digital preservation.
Ability to perform fast analysis on massive public blockchain transaction data is needed in various finance applications such as tracing of fraudulent activities. The blockchain data that is synced as a node is accessible as a sequence of blocks containing transactions. This way of accessing transaction data, however, is too slow for applications that require a transaction graph to be constructed. We develop a cluster based system that constructs a distributed transaction graph in parallel. Since blockchain data is continuously growing, our parallel system also offers the advantage of being able to scale by simply increasing the number of nodes in the cluster. Our system has been developed using the MPI message passing interface. We report performance results from our system operating on the whole 9.5 million block (roughly 4 year) Ethereum mainnet blockchain data. We report timings obtained from tests involving distributed transaction graph construction, partitioning, page ranking of addresses, degree distribution and token transaction counting on a 16 node economical cluster set up on the Amazon cloud. In particular, our system is able to construct distributed graph of 658 million ether and 31 major token transactions in 188 seconds.
Mirko Staderini, Caterina Palli, Andrea Bondavalli
Blockchain technology is having an ever-increasing impact on distributed applications domain, since the adoption of Blockchain 2.0 led to the spread of smart contracts. In such a context, Ethereum is the framework with the highest diffusion in terms of smart contract's development, with a consequent rise of exploitation of code vulnerabilities, some of which causing bad financial losses. For this reason, this paper focuses on the issues of Ethereum smart contracts implementation (made with the Turing-complete language Solidity), providing a comprehensive systematization of such vulnerabilities basing on a slice of the Common Weakness Enumeration (CWE). Moreover, some relevant propagation cases among different vulnerabilities and CWE groups, observed in exploited contracts, are highlighted.
In recent years, the Bitcoin (BTC) payment is increasingly popular in retailers and service providers. A BTC transaction (tx) needs six confirmations (one hour) to be validated, making it not suitable for fast-pay scenarios. Theoretically, a shorter waiting time period increases the success possibility of a double-spending attack. To address this problem, we propose BTCFast scheme to support fast BTC tx. BTCFast is a novel, decentralized, escrow-based scheme on top of the programmable smart contract (PSC)-enabled blockchains (e.g. Ethereum, EOS). We develop a smart contract (PayJudger) to work as a trusted payment judger, which guarantees the tx fairness. In addition, we devise a proof-of-work (PoW)-based payment judgment mechanism for PayJudger to resolve a BTC payment dispute. Our theoretical and experimental results show that BTCFast can reduce the waiting time to be less than 1 second with comparable security as the current approach (i.e., waiting for six confirmations) with no extra operation fee.
We propose Agora, the first privacy-aware data marketplace that enables parties to get compensated for contributing data, without relying on a trusted third party. We leverage cryptographic techniques to achieve three security properties: (i) data privacy-raw data remain private except for a function output, (ii) output verifiability-the output is proven to be correct, and (iii) atomicity of payments-parties cannot avoid paying for provided services. Agora is designed as a decentralized blockchain application via smart contracts. We implement a prototype on Ethereum and evaluate its performance in terms of computation overhead and monetary cost.
The block chain is an innovative technology which opened doors to new applications for solving numerous problems in distributed environments. In this work, we design a block chain based data storage and access framework Twitter application to remove its total dependence on a centralized repository. We use the public block chain and tools like Ganache, Metamask, Truffle and Ethereum IDE for deploying the contracts. In the proposed work, metadata of the files are stored on the block chain and we use the networks like Ropsten and Rinkebey for occurring the Transactions using a peer -to-peer networks. This will provide decentralized storage, distributed processing, and efficient lookup capabilities.
In this study, a novel blockchain-based platform for renewable energy investment is proposed. The blockchain technology has been shown to be a reliable way to send financial transactions across the world in a decentralized manner, at a fraction of the cost and with a faster transaction time. The proposed platform is capable of handling an equity-sharing investment program for solar PV projects. The platform distributes the electricity generation income by sending it over a blockchain. The Ethereum blockchain is used to create a prototype, which is a smart contract. The prototype is tested with a solar-PV electricity generation data. The result shows that the proposed platform can handle the expected transactions without an error. The overall performance of the proposed platform is tested by comparing its temporal duration and its financial costs with centralized solutions. Therefore, the proposed platform provides all the benefits mentioned at a much cheaper cost.
Abstract Blockchain technology has already changed industry and commercial enterprises remarkably. It is the underlying mechanism of a very well-known cryptocurrencies such as Bitcoin and Ethereum, and many other business applications. Therefore, its security draws the researchers’ attention more and more recently. One of Blockchain vulnerabilities is caused by weak randomness in ECDSA. A random number is not secure, cryptographically, which leads to a leakage in private key and even the user’s fund theft. As well the spam transaction attack may exploit the ECDSA weak randomness. This problem in security has been well known in cryptocurrencies community such as Bitcoin and fixed by applying RFC 6979 update in 2013. However, the problem is not entirely solved. The elliptic curve digital signature algorithm (ECDSA) was the first successful algorithm based on elliptic curve. This algorithm security depends on complexity of elliptic curve discrete logarithm problem (ECDLP). This algorithm applied in blockchain mechanism as a result of its low computational cost and short key. In this paper, we analyze the ECDSA weakness in blockchain and enhance its scheme by generating the signature with two secret keys. Using two secret keys will reduce the risk probability of revealing the secret key by knowing two messages. Therefore, the improved scheme can improve the security of the ECDSA.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Although Blockchain is still an emerging technology it has the potential to serve as a general purpose information technology platform. Already, smart contract / chaincode platforms, such as Ethereum and Hyperledger Fabric, provide support for the execution of arbitrary computations. However, the suitability of these platforms for specifying and enforcing data and service usage constraints (e.g., usage policies, regulatory obligations, societal norms) and providing guarantees with respect to conformance has yet to be determined. In order to address this gap, in this position paper we argue that symbolic artificial intelligence techniques in the form of semantic technology based policy languages and business process conformance tools and techniques, can together be used to provide guarantees with respect to the behaviour of autonomous smart contract / chaincode applications.
Ahmed Akhtar, Basit Shafiq, Jaideep Vaidya, Ayesha Afzal · 6 authors
The use of blockchain technology has been proposed to provide auditable access control for individual resources. However, when all resources are owned by a single organization, such expensive solutions may not be needed. In this work we focus on distributed applications such as business processes and distributed workflows. These applications are often composed of multiple resources/services that are subject to the security and access control policies of different organizational domains. Here, blockchains can provide an attractive decentralized solution to provide auditability. However, the underlying access control policies may be overlapping in terms of the component conditions/rules, and simply using existing solutions would result in repeated evaluation of user's authorization separately for each resource, leading to significant overhead in terms of cost and computation time over the blockchain. To address this challenge, we propose an approach that formulates a constraint optimization problem to generate an optimal composite access control policy. This policy is in compliance with all the local access control policies and minimizes the policy evaluation cost over the blockchain. The developed smart contract(s) can then be deployed to the blockchain, and used for access control enforcement. We also discuss how the access control enforcement can be audited using a game-theoretic approach to minimize cost. We have implemented the initial prototype of our approach using Ethereum as the underlying blockchain and experimentally validated the effectiveness and efficiency of our approach.
Many current mainstream blockchain systems, including Bitcoin, adopt Proof-of-Work (PoW) as their consensus protocol. Such a system faces various cryptoeconomic attacks, such as selfish mining. Previous studies have shown that with over 25% of the overall mining power, a selfish miner can benefit by gaining a proportion of rewards higher than its mining power in Bitcoin. This threshold is still higher than any current mining pool, and hence, selfish mining is not considered likely in Bitcoin. Unfortunately, this threshold is only applicable for a single attacker scenario, whereas in a realistic setting, multiple mining pools with significant hash power could perform selfish mining simultaneously. In this paper, we address this research gap by analyzing selfish mining scenarios with multiple independent attackers. Through extensive simulation studies, we show that when the number of selfish miners increases, each of them requires less mining power to gain an advantage, but that the range of mining power such that each selfish miner benefits becomes narrower and thus less sustainable. Our work is the first to show that in practice, there are scenarios where it is enough to have 12% mining power to benefit from selfish mining but also that having more than 7 selfish miners which benefit simultaneously is highly unlikely. We also infer that it is always beneficial for selfish miners to collude and build a more powerful mining pool than to mine independently. Additionally, we propose a safe limit for the size of mining pools in Bitcoin to avoid multi-player attacks. Finally, we extend our studies to Ethereum which uses a different reward model based on uncle blocks.