In order to solve the problems of copyrights infringement, high cost and complex process of rights protection in current media convergence center, a digital rights management system based on blockchain technology and IPFS (Inter Planetary File System) technology is proposed. Considering that large files such as video and audio cannot be stored on the blockchain directly, IPFS technology is adopted as the data expansion scheme for the data storage layer of the Ethereum platform, IPFS protocol is further used for distributed data storage and transmission of media content. In addition, smart contract is also used to uniquely identify digital rights through NFT (Non-fungible Tokens), which provides the characteristics of digital rights transferability and traceability, and realizes an open, transparent, tamper-proof and traceable digital rights management system for media convergence center. Several experimental results show that it has higher transaction success rate, lower storage consumption and transaction confirmation delay than existing scheme.
Open access
Advanced Steganography and Watermarking Techniques
Beibei Han, Yingmei Wei, Qingyong Wang, Francesco Maria De Collibus · 5 authors
Abstract In recent years, a surge of criminal activities with cross-cryptocurrency trades have emerged in Ethereum, the second-largest public blockchain platform. Most of the existing anomaly detection methods utilize the traditional machine learning with feature engineering or graph representation learning technique to capture the information in transaction network. However, these methods either ignore the timestamp information and the transaction flow direction information in transaction network or only consider single transaction network, the cross-cryptocurrency trading patterns in Ethereum are usually ignored. In this paper, we introduce a Multi-layer Temporal Transaction Anomaly Detection (MT $$^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow/> <mml:mn>2</mml:mn> </mml:msup> </mml:math> AD) model in Ethereum network with graph neural network. Specifically, for a given Ethereum token transaction network, we first extract its initial features including the structure subgraph and edge’s feature. Then, we model the temporal information in subgraph as a series of network snapshots according to the timestamp on each edge and time window. To capture the cross-cryptocurrency trading patterns, we combine the snapshots from multiple token transactions at a given timestamp, and we consider it as a new combined graph. We further use the graph convolution encoder with attention mechanism and pooling operation on this new graph to obtain the graph-level embedding, and we transform the anomaly detection on dynamic multi-layer Ethereum transaction networks as a graph classification task with these graph-level embeddings. MT $$^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow/> <mml:mn>2</mml:mn> </mml:msup> </mml:math> AD can integrate the transaction structure feature, edge’s feature and cross-cryptocurrency trading patterns into a framework to perform the anomaly detection with graph neural networks. Experiments on three real-world multi-layer transaction networks show that the proposed MT $$^2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mrow/> <mml:mn>2</mml:mn> </mml:msup> </mml:math> AD (0.8789 Precision, 0.9375 Recall, 0.4987 FbMacro and 0.9351 FbWeighted) can achieve the best performance on most evaluation metrics in comparison with some competing approaches, and the effectiveness in consideration of multiple tokens is also demonstrated.
Alfin Abdilah, Putri Anggun Sari, Ananto Tri Sasongko
This research is motivated by the difficulty of the Lazy Minting NFT process in the Rarible Marketplace. The NFT Lazy Mining process on the Rarible Marketplace can be said to be inefficient because the process still has to be done one by one. Not to mention other problems that arise such as wrong numbering and typing errors or typos. This resulted in the Lazy Minting NFT process on the Rarible Marketplace becoming less effective. This problem will make it difficult for NFT creators if they have a large number of digital works. Therefore, this research aims to build an automated NFT Lazy minting system on the Rarible Marketplace on the Ethereum Blockchain using AutoIt, so that the NFT Lazy minting process on the Rarible Marketplace becomes more effective and efficient. The method used in the development of the Lazy Minting NFT automation system in the Rarible Marketplace is Agile Development. This research resulted in a Lazy minting NFT automation system on the Rarible Marketplace on the Ethereum Blockchain. The conclusion of this study is that the application of this system is able to make the NFT Lazy mining process on the Rarible Marketplace more effective and efficient. This can make it easier for NFT creators in their NFT sales process.
The recent revolution in Industry 4.0 (IR 4.0) has characterized the integration of advance technologies to bring the fourth industrial revolution to scale the manufacturing landscape. There are different key drivers for this revolution, in this research we have explored the following among them such as, Industrial Internet of Things (IIoT), Deep Learning, Blockchain and Augmented Reality. The emerging concept from blockchain namely “Non-Fungible Token” (NFT) relating to the uniqueness of digital assets has vast potential to be considered for physical assets identification and authentication in the IR 4.0 scenario. Similarly, the data acquired through the deployment of IIoT devices and sensors into smart industry spectrum can be transformed to generated robust analytics for different industry use-cases. The predictive maintenance is a major scenario in which early equipment failure detection using deep learning model on acquired data from IIoT devices has major potential for it. Similarly, the augmented reality can be able to provide real-time visualization within the factory environment to gather real-time insight and analytics from the physical equipment for different purposes. This research initially conducted a survey to analyse the existing developments in these domains of technologies to further widen its horizon for this research. This research developed and deployed a smart contract into an ethereum blockchain environment to simulate the use-case for NFT for physical assets and processes synchronization. The next phase was deploying deep learning algorithms on a dataset having data generated from IIoT devices and sensors. The Feedforward and Convolutional Neural Network were used to classify the target variables in relation with predictive maintenance failure analysis. Lastly, the research also proposed an AR based framework for the visualization ecosystem within the industry environment to effectively visualize and monitory IIoT based equipment’s for different industrial use-cases i.e., monitoring, inspection, quality assurance.
In recent years, Bitcoin and other cryptocurrencies like Ethereum and Dogecoin have emerged as important asset classes in general, and diversification and hedging instruments in particular. The recent COVID-19 pandemic has provided the chance to examine and assess cryptocurrencies’ behavior during extremely stressful times. The methodology of this study is based on an estimate using the ARDL model from 22 January 2020 to 12 March 2021, allowing us to analyze the long-term and short-term relationship between cryptocurrencies and COVID-19. Our results demonstrate that there is cointegration between the chosen cryptocurrencies in the market and COVID-19. The results indicate that Bitcoin, ETH, and DOGE prices were affected by COVID-19, which means that the pandemic seriously affected the three cryptocurrency prices.
The Ethereum blockchain and its ERC20 token standard have revolutionized the landscape of digital assets and decentralized applications. ERC20 tokens developed on the Ethereum blockchain have gained significant attention since their introduction. They are programmable and interoperable tokens, enabling various applications and token economies. Transaction graphs, representing the flow of the value between wallets within the Ethereum network, have played a crucial role in understanding the system's dynamics, such as token transfers and the behavior of traders. Here, we explore the evolution of daily transaction graphs of ERC20 token transactions, which sheds light on the trader's behavior during the Black Swan Events -- 2018 crypto crash and the COVID-19 pandemic. By using the tools from network science and differential geometry, we analyze 0.98 billion of ERC20 token transaction data from November 2015 to January 2023. Our analysis reveals that ERC20 financial ecosystem has evolved from a localized wealth formation period to a more mature financial ecosystem where wealth has dispersed among the traders in the network after the crypto crash and during the pandemic period. Before the crash, most sellers only sell the tokens, and buyers only buy the tokens. However, after the crash and during the pandemic period, sellers and buyers both performed buying and selling activities. In addition, we observe no significant negative impact of the COVID-19 pandemic on user behavior in the financial ecosystem.
When migrating smart contracts from one blockchain platform to another, there are potential security risks. This is because different blockchain platforms have different environments and characteristics for executing smart contracts. The focus of this paper is to study the security risks associated with the migration of smart contracts from Ethereum to Arbitrum. We collected relevant data and analyzed smart contract migration cases to explore the differences between Ethereum and Arbitrum in areas such as Arbitrum cross-chain messaging, block properties, contract address alias, and gas fees. From the 36 types of smart contract migration cases we identified, we selected four typical types of cases and summarized their security risks. The research shows that smart contracts deployed on Ethereum may face certain potential security risks during migration to Arbitrum, mainly due to issues inherent in public blockchain characteristics, such as outdated off-chain data obtained by the inactive sequencer, logic errors based on time, failed permission checks, and denial of service (DOS) attacks. To mitigate these security risks, we proposed avoidance methods and provided considerations for users and developers to ensure a secure migration process. It is worth noting that this study is the first to conduct an in-depth analysis of the secure migration of smart contracts from Ethereum to Arbitrum.
Abstract This article examines the causal relationship between stock indices and cryptocurrencies during the current war between Russia and Ukraine. The econometric investigation runs from February 24, 2022 to April 12, 2023, focusing on seven stock market indices (S&P500, DAX, CAC40, Nikkei, TSX, MOEX and PFTS) and seven cryptocurrencies (Bitcoin, Ethereum, Litcoin, Dash, Ripple, DigiByte and XEM). In this article, we try to understand how investors react to fluctuations in financial assets to seek safe havens in crypto currencies. We used dynamic causality in the Granger (1969) sense to detect a possible causal relationship in the short term, and seven models to estimate the long-term relationship between cryptocurrencies and financial assets. The causal relationship between financial market indexes and cryptocurrency coins in the short run indicate that three famous cryptocurrencies (BITCOIN, ETHEREUM, RIPPLE) and the two digital asset with minor popularity (XEM, Digibyte) are impacted by the German, Russian and Ukrainian stock markets. In the long-run we found a positive and significate effect of the American, Canadian, French and Ukrainian stock market indexes on Bitcoin. Thus, the stability of the traditional financial markets during the current war period can be explained on the one hand by investors’ fears of an unstable business climate, and on the other hand, by speculators’ sentiment towards new electronic products which are perceived as hedging instruments and a safe haven in the face of the conflict between Ukraine and Russia. JEL Classifcation: C5 · C22 · G1
Open access
Environmental and Biological Research in Conflict Zones
Mingzhe Wei, Ioannis Kyriakou, Georgios Sermpinis, Charalampos Stasinakis
Abstract This study explores the effectiveness of technical and fundamental analysis in predicting and trading the returns of 12 cryptocurrencies, namely Bitcoin, Ethereum, Ripple, Dash, Cardano, Avalanche, Binance Coin, Dogecoin, Polkadot, Litecoin, Terra and Solana. A universe of 7846 technical rules, five log moving average‐based ratios and 59 fundamental factors are used to test predictability and profitability through the Lucky Factors methodology and Superior Predictive Ability test. We observe predictability for a small set of technical and fundamental rules, while only the short‐term log moving average‐based ratio and Hashrate Index demonstrate genuine in‐sample and out‐of‐sample profitability. Our findings question the value of both technical and fundamental analysis on cryptocurrencies.
Zhijian Liu, Zihan Shen, Hongfei Wang, Qianjia Zou
With the increasing amount and trading volume, account security has become an issue that people have to consider. The security of Ethereum is discussed in four different aspects. This paper reviews the application of cryptography in Ethereum, including the importance of relevant hash algorithms and digital signature techniques for securing data. The basic structure of the Merkle Tree and the role of its modified data structure, performed in the security mechanism of Ethereum are also analyzed. This paper also analyzes the related Merkle Proof algorithm. Additionally, the definition and working mechanism of Gas in Ethereum are also provided, through which the operating mechanism and creation method of Gas can guarantee the security of Ethereum's processing power. Finally, this paper indicates the underlying vulnerabilities and possible attacks on Bitcoin and Ethereum, including double spending attacks under proof of work and further introduces the related solutions. This paper can provide researchers good references on Ethereum security problem.
This article discusses Ethereum Ghost Protocol, a technology that promises faster mining speeds. The Ghost protocol enables different crypto miners to create valid blocks concurrently. The article explains why the protocol reduces the delay in traditional blockchains through stale or uncle blocks. It explains why the Ghost Protocol is faster than Bitcoin. It also introduces areas in which Ethereum Ghost Protocol can work, such as insecure environments and Internet of Things (IoT). Besides, the paper defines centralization bias and explains how the Ghost Protocol solves the problem. Since the Ghost Protocol is decentralized and stores information in multiple nodes, it is more secure. Besides, it is scalable and saves storage space. Despite these benefits, this paper discusses two significant challenges, including slow transactions and difficulties in coding. However, the Ghost protocol will enhance cryptocurrency due to the ease of mining, enhanced security, and other benefits to miners. Overall, the paper suggests the need to embrace the Ghost protocol in the blockchain.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
This paper presents the design and implementation of a monitoring and data collection system for agricultural product preservation during transportation to meet authenticity and traceability requirements. The system is built and performed using blockchain and Internet of Things (IoT) technology to use and integrate their benefits. This system comprises a private blockchain network built on the Ethereum platform and powered by the GoQuorum protocol, which enables distributed data exchange among members using a common protocol and cryptographic techniques while ensuring the transparency and integrity of the information. A wireless sensor network has been designed and implemented for collecting data from sensors about the storage environment of agricultural products. This study also proposes using LoRa technology to build low-cost wireless communication networks with broad coverage for data collection from sensor nodes mounted to agricultural products. Furthermore, the integrated online map web assists in real-time monitoring and tracing of information on the process of transporting agricultural products, as well as querying data for completed contracts. Experiments were conducted close to the reality of the application’s desire to deploy the system to calibrate and evaluate the functioning, with promising results.
Non-fungible tokens(NFTs) are on the rise. They can represent artworks exhibited for marketing purposes on webpages of companies or online stores -- analogously to physical artworks. Lending of NFTs is an attractive form of passive income for owners but comes with risks (e.g., items are not returned) and costs for escrow agents. Similarly, renters have difficulties in anticipating the impact of artworks, e.g., how spectators of NFTs perceive them. To address these challenges, we introduce an NFT rental solution based on a pay-per-like pricing model using blockchain technology, i.e., smart contracts based on the Ethereum chain. We find that blockchain solutions enjoy many advantages also reported for other applications, but interestingly, we also observe dark sides of (large) blockchain fees. Blockchain solutions appear unfair to niche artists and potentially hamper cultural diversity. Furthermore, a trust-cost tradeoff arises to handle fraud caused by manipulation from parties outside the blockchain. All code for the solution is publicly available at: https://github.com/asopi/rental-project
Javier Arcenegui, Rosario Arjona, Iluminada Baturone
Ethereum is a dynamic blockchain that grows every day thanks to a community that creates and decides on various of its issues. The community participates through Ethereum Improvement Proposals (EIPs) at many levels, from proposals that describe new standards for the creation of new tokens to proposals that define new ways for the Ethereum main network to generate new blocks. This paper describes how an Ethereum Request for Comments (ERC)-type EIP, the ERC-4519, was proposed last year to standardize the way to define non-fungible tokens (NFTs) representing assets that can generate their own Ethereum addresses and obey users and owners. Advantages provided by ERC-4519 in several use cases are illustrated. The examples show the facilities and the security improvements introduced in the management of both physical and digital assets by their owners and users. Particularly, use cases with physical assets such as IoT devices are illustrated.
Mallikarjun Reddy Dorsala, V. N. Sastry, Sudhakar Chapram
With the rapid development of cloud computing, vast amounts of duplicated data are being uploaded to the cloud, wasting storage resources. Deduplication (dedup) is an efficient solution to save storage costs of cloud storage providers (CSPs) by storing only one copy of the uploaded data. However, cloud users do not benefit directly from dedup and may be reluctant to dedup their data. To motivate the cloud users towards dedup, CSPs offer incentives on storage fees. The problems with the existing dedup schemes are that they do not consider: (1) correctness - the incentive offered to a cloud user should be computed correctly without any prejudice. (2) fairness - the cloud user receives the file link and access rights of the uploaded data if and only if the CSP receives the storage fee. Meeting these requirements without a trusted party is non-trivial, and most of the existing dedup schemes do not apply. Another drawback is that most of the existing schemes emphasize incentives to cloud users but failed to provide a reliable incentive mechanism. As public Blockchain networks emulate the properties of trusted parties, in this paper, we propose a new Blockchain-based dedup scheme to meet the above requirements. In our scheme, a smart contract computes the incentives on storage fee, and the fairness rules are encoded into the smart contract for facilitating fair payments between the CSPs and cloud users. We prove the correctness and fairness of the proposed scheme. We also design a new incentive mechanism and show that the scheme is individually rational and incentive compatible. Furthermore, we conduct experiments by implementing the designed smart contract on Ethereum local Blockchain network and list the transactional and financial costs of interacting with the designed smart contract.
M. K. Ghosh, Dyuti Ghosh, Raju Halder, Joydeep Chandra
The recent surge of Ethereum in prominence has made it an attractive target for various kinds of crypto-crime. Phishing scams, for example, are an increasingly prevalent cybercrime in which malicious users attempt to steal funds from a user's crypto wallet. This research investigates the effects of network architectural features as well as the temporal aspects of user activities on the performance of detecting phishing users on the Ethereum transaction network. We employ traditional machine learning algorithms to evaluate our model on real-world Ethereum transaction data. The experimental results demonstrate that our proposed features identify phishing accounts efficiently and outperform the baseline models by 4% in Recall, and 5% in F1-score.
Ethereum has established itself as a highly decentralized and reliable blockchain network and serves as the de facto standard. However, using public blockchains in enterprise applications can be challenging due to concerns about confidentiality and transaction finality. As a result, consortium and private blockchains, which limit participation to specific nodes, are also commonly used. But these consortium blockchains also have limitations, such as limited node participation due to performance constraints imposed by the consensus algorithm. In this study, by using ZK-rollups as a messaging means, we would connect consortium blockchains via public Ethereum as a hub. We examined a mechanism to balance both mathematically reliable interoperability and maintaining the secrecy of the information and the finality. The concept was actually implemented, to confirm the interoperability of simple money transfer transactions. And also, the way to handle secret information and the finality was theoretically organized.
The number of money laundering crimes for Ethereum and the amount involved have grown exponentially in recent years. However, previous studies related to anomaly detection for Ethereum usually consider multiple types of financial crimes as a whole, ignoring the apparent differences between money laundering and other malicious activities and lacking a more granular detection targeting money laundering. In this paper, for the first time, we propose an improved graph embedding algorithm specifically for money laundering detection called GTN2vec. By mining Ethereum transaction records, the algorithm comprehensively considers the behavioral patterns of money launderers and structural information of transaction networks and can automatically extract features of money laundering addresses. Specifically, we fuse the gas price and timestamp from the transaction records into a new weight and set appropriate return and exploration parameters to modulate the sampling tendency of random walk to characterize the money laundering nodes. We construct the dataset using real Ethereum data and evaluate the effectiveness of GTN2vec on the dataset by various classifiers such as random forest. The experimental results show that GTN2vec can accurately and effectively extract money laundering account features and significantly outperform other advanced graph embedding methods.
The data traffic has increased significantly along with the quick development of smart wireless technologies, and current 5G networks are still not completely prepared to handle future huge data traffic in the areas of services, data transfer, data storage, and processing. 6G is expected to offer very high-level extended 5G capabilities, such as a Tbps data transfer rate and a sub-millisecond response time. The main objective of this study is to be aware of new technologies being enhanced day by day and provide existing research content, issues, and directions for the future regarding 6G wireless networks. Therefore, a systematic literature review of research articles is provided by categorizing the selected studies published between 2019 and 2022 in terms of enabling technologies. First, the researcher discussed the need for 6G by predicting the explosive growth of mobile traffic from 2022 to 2030. Second, 6G requirements, trends, and services are addressed and contrasted with 5G in terms of a group of key performance indicators. Third, conduct a comparative analysis of 6G challenges and gaps, such as security and privacy, the need for a decentralized network, Omnipresent service coverage, and storage efficiency. So, it is essential to develop an accurate, faster, and well-organized system for the 6G wireless network. We have presented an efficient and secure mode R6GS, which combines blockchain and 6G to improve security from the lower to upper layers while also improving storage efficiency. Cybertwin technologies are used at the edge layer of the 6G network in the proposed model R6GS to improve security. The smart contracts, IPFS and Ethereum blockchain are used in the proposed R6GS model to enhance the 6G network's data integrity and data storage. It also processes and stores massive amounts of data at various network layers, which removes the large storage capacity issue of traditional P2P and Client/Server (C/S) networks due to centralized servers in 6G technology. For the performance evaluation, the model is evaluated through expert opinion. Moreover, the proposed R6GS model also improves time efficiency through the edge layer, because if a task is available at the edge layer, there is no need to send a request to the core layer. The server at the edge layer efficiently delivers data to end nodes. Furthermore, a taxonomy is presented in this study. To the best of our knowledge, the proposed methodology worked efficiently.
Augusto Sampaio, Pedro Antonino, Juliandson Ferreira, Filipe Arruda · 5 authors
We present a framework that supports the safe deployment and upgrade of smart contracts based on the design-by-contract paradigm. The starting point is an interface specification with invariants and pre- and postconditions for each function. The first deployed smart contract must conform to this specification. Specification evolution might involve both changing the data representation as well as extending the interface with new functions, provided the evolved specification is a refinement of the original one. Implementation evolution must conform to the corresponding specification. We report on the applicability of the framework in the verification of smart contracts that implement some Ethereum standards.
The implementation of statistical techniques in on-line surveillance of financial markets has been frequently studied more recently. As a novel approach, statistical control charts which are famous tools for monitoring industrial processes, have been applied in various financial applications in the last three decades. The aim of this study is to propose a novel application of control charts called profile monitoring in the surveillance of the cryptocurrency markets. In this way, a new control chart is proposed to monitor the price variation of a pair of two most famous cryptocurrencies i.e., Bitcoin (BTC) and Ethereum (ETH). Parameter estimation, tuning and sensitivity analysis are conducted assuming that the random explanatory variable follows a symmetric normal distribution. The triggered signals from the proposed method are interpreted to convert the BTC and ETH at proper times to increase their total value. Hence, the proposed method could be considered a financial indicator so that its signal can lead to a tangible increase of the pair of assets. The performance of the proposed method is investigated through different parameter adjustments and compared with some common technical indicators under a real data set. The results show the acceptable and superior performance of the proposed method.
The development of an electronic voting system that would replace traditional election procedures is a research topic of great interest for many years. Blockchain technology could provide some guarantees and fulfill strong requirements for electronic voting platforms, such as transparency, immutability, and confidentiality. From time to time research is conducted to address problems in voting systems. Many research works attempt to implement secure and reliable voting systems, which address known security, anonymity, and fraud issues that might threaten such systems. This paper presents a proposal of a secure electronic voting system, the EtherVote, using the Ethereum Blockchain network that focuses deeply on the field of identification of eligible citizens. The proposed system will be entirely based on Blockchain without any central authority servers or databases, thus improving security, privacy, and election cost. Limitations, problems, and solutions are discussed, in order to make the proposed electronic voting system ideal and ready to use for national elections.
Bruno Medeiros de Oliveira, Pedro Antonino, Augusto Sampaio
Transaction costs are a barrier to the wide adoption of decentralized applications. To address this issue, this paper proposes a framework to optimize transaction fees by carrying out a conflict-avoiding packaging of multiple smart-contract calls into a single transaction. It relies on two main concepts: a way to optimize the bundling of transactions with a conflict-avoiding packaging strategy and a way to execute such bundles with a package-processing methodology. We illustrate our framework and the gas economy it can bring with a case study where we analyze a popular Ethereum smart contract.