Blockchain systems suffer from high storage costs as every node needs to store and maintain the entire blockchain data. After investigating Ethereum's storage, we find that the storage cost mostly comes from the index, i.e., Merkle Patricia Trie (MPT). To support provenance queries, MPT persists the index nodes during the data update, which adds too much storage overhead. To reduce the storage size, an initial idea is to leverage the emerging learned index technique, which has been shown to have a smaller index size and more efficient query performance. However, directly applying it to the blockchain storage results in even higher overhead owing to the requirement of persisting index nodes and the learned index's large node size. To tackle this, we propose COLE, a novel column-based learned storage for blockchain systems. We follow the column-based database design to contiguously store each state's historical values, which are indexed by learned models to facilitate efficient data retrieval and provenance queries. We develop a series of write-optimized strategies to realize COLE in disk environments. Extensive experiments are conducted to validate the performance of the proposed COLE system. Compared with MPT, COLE reduces the storage size by up to 94% while improving the system throughput by $1.4\times$-$5.4\times$.
Dominic Grandjean, Lioba Heimbach, Roger Wattenhofer
In September 2022, Ethereum transitioned from Proof-of-Work (PoW) to Proof-of-Stake (PoS) during "the merge" - making it the largest PoS cryptocurrency in terms of market capitalization. With this work, we present a comprehensive measurement study of the current state of the Ethereum PoS consensus layer on the beacon chain. We perform a longitudinal study of the history of the beacon chain. Our work finds that all dips in network participation are caused by network upgrades, issues with major consensus clients, or issues with service operators controlling a large number of validators. Further, our longitudinal staking power decentralization analysis reveals that Ethereum PoS fairs similarly to its PoW counterpart in terms of decentralization and exhibits the immense impact of (liquid) staking services on staking power decentralization. Finally, we highlight the heightened security concerns in Ethereum PoS caused by high degrees of centralization.
In May 2022, an apparent speculative attack, followed by market panic, led to the precipitous downfall of UST, one of the most popular stablecoins at that time. However, UST is not the only stablecoin to have been depegged in the past. Designing resilient and long-term stable coins, therefore, appears to present a hard challenge. To further scrutinize existing stablecoin designs and ultimately lead to more robust systems, we need to understand where volatility emerges. Our work provides a game-theoretical model aiming to help identify why stablecoins suffer from a depeg. This game-theoretical model reveals that stablecoins have different price equilibria depending on the coin's architecture and mechanism to minimize volatility. Moreover, our theory is supported by extensive empirical data, spanning $1$ year. To that end, we collect daily prices for 22 stablecoins and on-chain data from five blockchains including the Ethereum and the Terra blockchain.
Rasoul Amirzadeh, Dhananjay Thiruvady, Asef Nazari, Mong Shan Ee
Abstract Cryptocurrencies have gained widespread attention, particularly in finance and investment sectors. Despite their growing popularity, cryptocurrencies can be a high-risk investment due to their price volatility. The inherent volatility in cryptocurrency prices, coupled with the effects of external global economic factors, makes predicting their price movements challenging. To address this challenge, we propose a dynamic Bayesian network (DBN)-based approach to uncover potential causal relationships among various features including social media data, traditional financial market factors, and technical indicators. This study focuses on six major cryptocurrencies, including Bitcoin, Binance Coin, Ethereum, Litecoin, Ripple, and Tether. The proposed model’s performance is compared to five baseline models of auto-regressive integrated moving average, support vector regression, long short-term memory, random forests, support vector machines, and a large language model. Results demonstrate that while DBN performance varies across cryptocurrencies, with some cryptocurrencies exhibiting higher predictive accuracy than others, the DBN significantly outperforms the baseline models.
The purpose of this project is to develop Crypto Market, an innovative online shopping site thataccepts Ethereum payments using Web3 technologies. The approach included using ReactJS for front-enddevelopment, integrating WalletConnect and MetaMask for secure purchases, and using the PostgreSQLdatabase with the Django Rest framework for efficient data management. The goal was to create an easyto-learn interface that would appeal to a wide range of users. The main results of the project were thesuccessful integration of WalletConnect and MetaMask, which allow users to securely transfer Ethereumfrom their personal wallets to the site’s pool wallet with minimal transaction fees. The integration ofCoinGecko has increased transparency for customers by showing them the real-time dollar equivalent ofthe Ethereum price on product pages. Additionally, the existence of a membership system enabled userregistration and facilitated store opening requests, providing access to a dedicated panel for productmanagement for approved vendors. Important results from this research show that Web3 technologies offera secure shopping experience using Ethereum. WalletConnect and MetaMask integration provided areliable environment for transactions, minimizing the risk of failed or incorrect payments. The successfuladoption of cryptocurrency as a payment method in the context of online shopping highlights the potentialof decentralized finance in traditional e-commerce applications. In summary, the Crypto Market projectdemonstrates the advantages and feasibility of incorporating cryptocurrency payments into online shoppingsites. With this research, it has been revealed that cryptocurrencies should be more involved in commercialtransactions and that they are a system that can be easily integrated.
Abstract: This research paper aims to assess the environmental sustainability of Polygon's consensus mechanism and transaction processing, comparing its energy consumption and carbon footprint with other Layer 2 and Layer 1 blockchain solutions. The growing popularity of blockchain technology has raised concerns about its significant energy consumption and environmental impact. As a Layer 2 scaling solution, Polygon has gained traction for its ability to enhance scalability and reduce transaction costs on the Ethereum network. However, its environmental sustainability remains a critical aspect that needs evaluation. To begin, an in-depth environmental impact assessment is conducted to analyze the energy consumption and carbon footprint associated with Polygon's consensus mechanism and transaction processing. Data on energy consumption is collected and compared with other Layer 2 and Layer 1 blockchain solutions. Through quantitative analysis, the carbon emissions produced by Polygon's operations are quantified and compared to industry benchmarks. This assessment provides a baseline for evaluating Polygon's environmental performance. The research then delves into a comparative analysis, examining the energy consumption efficiency of Polygon's consensus mechanism in relation to other blockchain solutions. This analysis includes an assessment of scalability and transaction throughput, considering the trade-offs between energy consumption and network performance. By comparing Polygon with other Layer 2 and Layer 1 blockchain solutions, insights are gained into the environmental advantages and challenges posed by Polygon's consensus mechanism. Furthermore, potential avenues for optimizing Polygon's consensus mechanism and transaction processing are explored. The research explores innovative techniques and improvements that could enhance the sustainability of Polygon's operations. These optimization strategies focus on reducing energy consumption and minimizing the carbon footprint. Additionally, the feasibility and benefits of integrating renewable energy sources into Polygon's infrastructure are investigated. The potential of renewable energy integration to contribute to sustainable transaction processing is examined, considering challenges and opportunities. Governance and policy considerations play a crucial role in promoting environmental sustainability within Polygon's ecosystem. This research evaluates the governance structures and policies that influence sustainable practices within Polygon. The decision-making processes and mechanisms driving sustainability-related initiatives are analyzed, highlighting the importance of effective governance in driving environmental sustainability. Economic incentives and rewards are also explored as mechanisms to encourage sustainable practices within Polygon's ecosystem. The research examines existing economic incentives and mechanisms designed to incentivize energy efficiency and carbon reduction. The effectiveness of these incentives is evaluated, and potential strategies for further incentivization are discussed. The economic aspects of sustainability are crucial in encouraging stakeholders to prioritize environmental concerns
Khaled Ahmed, Sabry F. Saraya, John F. Wanis, Hesham Ali
Open finance is evolving and extending open banking. This creates a large context that implies a financial and identity data exchange paradigm, which faces challenges to balance customer experience, security, and the self-control over personal identity information. We propose Self-Sovereign Banking Identity (SSBI), a Blockchain-based self-sovereign identity (SSI) to secure private data sharing by utilizing trusted customer’s banking cards as a key storage and identity transaction-signing enclave. The design and implementation of the SSI framework is based on the Veramo SDK and Ethereum to overcome the limitation of signing curve availability on the current banking Java Cards needed for Hyperledger Indy. SSBI uses the elliptic curve SECP256K1 for transaction signing, which exists for several payment cards in the market. SSBI enables automated financial services and trust in the service provider communication. This work analyzes the flow and framework components, and evaluates the usability, integration, and performance in terms of throughput, latency, security, and complexity. Furthermore, the proposed approach is compared with related solutions. The presented prototype implementation is based on a test Ethereum network and signing transactions on the banking card. The preliminary results show that SSBI provides an effective solution for integrating the customer’s banking cards to secure open banking identity exchange. Furthermore, it allows the integration of several scenarios to support trusted open banking. The Blockchain layer settings need to be scaled and improved before real-world implementation.
Monika di Angelo, Thomas Durieux, João F. Ferreira, Gernot Salzer
Smart contracts are blockchain programs that often handle valuable assets. Writing secure smart contracts is far from trivial, and any vulnerability may lead to significant financial losses. To support developers in identifying and eliminating vulnerabilities, methods and tools for the automated analysis of smart contracts have been proposed. However, the lack of commonly accepted benchmark suites and performance metrics makes it difficult to compare and evaluate such tools. Moreover, the tools are heterogeneous in their interfaces and reports as well as their runtime requirements, and installing several tools is time-consuming. In this paper, we present SmartBugs 2.0, a modular execution framework. It provides a uniform interface to 19 tools aimed at smart contract analysis and accepts both Solidity source code and EVM bytecode as input. After describing its architecture, we highlight the features of the framework. We evaluate the framework via its reception by the community and illustrate its scalability by describing its role in a study involving 3.25 million analyses.
Chihiro Kado, Naoto Yanai, Jason Paul Cruz, Kyosuke Yamashita · 5 authors
Vulnerabilities of Ethereum smart contracts often cause serious financial damage. Whereas the Solidity compiler has been updated to prevent vulnerabilities, its effectiveness has not been revealed so far, to the best of our knowledge. In this paper, we shed light on the impact of compiler versions of vulnerabilities of Ethereum smart contracts. To this end, we collected 503,572 contracts with Solidity source codes in the Ethereum blockchain and then analyzed their vulnerabilities. For three vulnerabilities with high severity, i.e., Locked Money, Using tx.origin, and Unchecked Call, we show that their appearance rates are decreased by virtue of major updates of the Solidity compiler. We then found the following four key insights. First, after the release of version 0.6, the appearance rate for Locked Money has decreased. Second, regardless of compiler updates, the appearance rate for Using tx.origin is significantly low. Third, although the appearance rate for Unchecked Call has decreased in version 0.8, it still remains high due to various factors, including code clones. Fourth, through analysis of code clones, our promising results show that the appearance rate for Unchecked Call can be further decreased by removing the code clones.
Shu Pan, Nurul Izzatul Lydia Binti Za’ba, M. Yaacob
Disputes in the construction industry occur from time to time. The development of the building information model enables the information in the process of project execution in the construction industry to be stored in the same model, which can find appropriate communication channels for disputes between different parties involved in engineering projects. As an emerging technology, Blockchain has received wide attention and is widely used in various fields because of its distributed storage, decentralization, and de-trust characteristics. Furthermore, smart contracts technology provides a new solution to the existing difficulties of disputes in the construction engineering industry from the perspective of replacing traditional contracts. Based on the research of Blockchain and smart contracts technology, this paper analyzes the feasibility of applying Blockchain and smart contracts to contracts management of the construction information model and discusses the implementation plan of combining Blockchain and contracts management of the construction information model with the actual scenario of material supply in the construction industry, choosing Ethereum blockchain platform as the underlying architecture and adopting " The development of smart contracts for construction material supply is carried out by adopting the "on-chain off-chain" data storage and business interaction method, and the specific design and implementation are carried out from the perspectives of system architecture, system deployment, contracts invocation mechanism, and contracts function.
Open access
Legal, Health, Environmental and COVID-19 Challenges
Alexander Shevtsov, Despoina Antonakaki, Ioannis Lamprou, Ioannis Kontogiorgakis · 6 authors
On 24 February 2022, Russia invaded Ukraine, starting what is now known as the Russo-Ukrainian War, initiating an online discourse on social media. Twitter as one of the most popular SNs, with an open and democratic character, enables a transparent discussion among its large user base. Unfortunately, this often leads to Twitter's policy violations, propaganda, abusive actions, civil integrity violation, and consequently to user accounts' suspension and deletion. This study focuses on the Twitter suspension mechanism and the analysis of shared content and features of the user accounts that may lead to this. Toward this goal, we have obtained a dataset containing 107.7M tweets, originating from 9.8 million users, using Twitter API. We extract the categories of shared content of the suspended accounts and explain their characteristics, through the extraction of text embeddings in junction with cosine similarity clustering. Our results reveal scam campaigns taking advantage of trending topics regarding the Russia-Ukrainian conflict for Bitcoin and Ethereum fraud, spam, and advertisement campaigns. Additionally, we apply a machine learning methodology including a SHapley Additive explainability model to understand and explain how user accounts get suspended.
Вступ. Криптовалюти, такі як Bitcoin, Ethereum та інші, з’явилися на світовому фінансовому ринку близько десяти років тому і з тих пір стали предметом великої уваги. Ці цифрові валюти привернули увагу не лише інвесторів, а й фахівців з фінансів та економіки, які досліджують їх вплив на міжнародні фінансові ринки. Мета. Аналіз впливу криптовалюти на міжнародні фінансові ринки. Наукова новизна. Полягає у всебічному аналізі впливу криптовалюти на міжнародні фінансові ринки в контексті регулювання та регуляторної політики урядів та міжнародних організацій. Робота містить нові результати, які були отримані завдяки аналізу останніх досліджень та статистичних даних, що забезпечує її важливість у розумінні взаємозв’язку криптовалюти та міжнародних фінансових ринків. Результати дослідження. В результаті дослідження було встановлено, що регулювання криптовалютного ринку має значний вплив на міжнародні фінансові ринки. З одного боку, регулювання може забезпечити більшу стабільність на ринку криптовалюти та знизити ризики для інвесторів, що може позитивно вплинути на загальний фінансовий ринок. З іншого боку, неправильне регулювання може призвести до великих коливань цін на криптовалюту та зростання ризиків для інвесторів, що може негативно вплинути на міжнародний фінансовий ринок. Дослідження також показало, що регулювання криптовалютного ринку відрізняється в різних країнах та може мати різний вплив на міжнародний фінансовий ринок. Деякі країни активно регулюють криптовалютний ринок та намагаються забезпечити більшу стабільність на ньому, тоді як інші країни намагаються заборонити криптовалюту або дозволяють торгівлю на незареєстрованих біржах, що може призвести до збільшення ризиків для інвесторів. Також було виявлено, що криптовалюти можуть мати значний вплив на загальний міжнародний фінансовий ринок, зокрема на біржові курси валют та інші фінансові інструменти. Водночас, криптовалюта також може використовуватись як інструмент для захисту від інфляції та інших ризиків на міжнародному фінансовому ринку. Отже, результати дослідження показують, що регулювання криптовалютного ринку має значний вплив на міжнародні фінансові ринки.
The electronic money, digital cloud payments, banknote redesign policies and currency in circulation vis-à-vis relevance of cashless system and technology acceptance theory in Nigeria is a rarely covered topic. Design policies are used by central banks to give direction to the design process of banknotes. The study of the banknote design policies of the past century shows that ‘technology-centred policies’ are gaining popularity. Even cryptocurrencies such as Bitcoin, Ethereum, Facebook’s Diem, Corda, Fabric and Ripple are competing for a spot in the cashless world, constantly reinventing themselves in the hope of offering more stable value, and quicker, cheaper settlement (Chapman, 2021; (Shao et al., 2021; Zhang & Huang, 2021). The sole aim of introducing digital currency is to reduce the volume of physical currency in circulation which in turn destabilizes socioeconomic development of a country (Barontini & Holden, 2019). It is well-known fact that many people and businesses don’t accept innovations especially the ones caused by technology. Finally, from the literatures reviewed, the redesigning of the Naira is for economic reasons which is not limited to reducing inflation, combating counterfeiting, checking financial insecurity and reducing the money in circulation. There has been a wide acceptance of electronic banking in Nigerian banks and technology has become more popular as service offering to customers have become more convenient, thereby, leading to an increase in competitiveness and profitability. There is a swift variation in the method of conducting business globally and in Nigeria, particularly which is borne from advancement in e-banking. Awolusi and Aduaka (2020) has said that it is becoming progressively difficult to satisfy customer expectations. The cashless economy does not imply an outright end to the circulation of cash (or money) in the economy but that of the operation of a banking system that keeps cash transactions to
Gelişen teknolojinin sağladığı olanaklar sayesinde internet kullanımıyla gerçekleştirilen işlemlerde artış olmuş ve bu da verilerde artışa neden olmuştur. Bu durum işletmeler için verilerin güvenli bir şekilde saklanması, paylaşılması, kontrolünün sağlaması ve yönetilmesine yönelik yeni teknoloji ihtiyacı doğurmuştur. Bu kapsamda faydalanılabilecek güncel teknolojilerden birisi de blok zinciri (Blockchain) yapısıdır. Blok zinciri yapısı birçok alanda kullanılabilecek bir teknoloji olup günümüzde en popüler kullanım alanı kripto paralar üzerinde olmaktadır. Bu çalışmada önemli alt kripto para birimlerinden biri olan Polkadot kripto para birimi için tahminleme işlemi yapılması amaçlanmıştır. Yapılan çalışmada 20.08.2020 ve 27.02.2023 tarihleri arasındaki veriler kullanılmış olup, bu verilere göre çıktı değer olarak günlük ortalama Polkadot değerinin tahmin edilmesi amaçlanmıştır. Girdi değerleri için kümeler iki farklı şekilde oluşturulmuştur. İlk girdi değerlerinde; Polkadot YouTube arama sayısı, Polkadot Google arama sayısı ve Polkadot hacmi kullanılmıştır. İkinci girdi değerlerinde ise ilk girdi değerlerinden farklı olarak alt kripto paraların lideri Ethereum eklenmiştir. İki farklı girdi yapısından oluşan bu çalışmada Polkadot para birimi günlük ortalama değerlerinin tahminlenebilmesi için yapay sinir ağlarında çok katmanlı algılayıcılar ile derin öğrenme yöntemlerinden olan uzun kısa süreli bellek yapısı kullanılarak tahminleme çalışması yapılmıştır. Sonuçlar incelendiğinde elde edilen yapay sinir ağlarında 4 girdi kümesinden oluşan değerlerin 0,93 korelasyon katsayısı ile daha iyi sonuç verdiği belirlenmiştir.
Open access
Currency Recognition and Detection
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
The education management model refers to the system and processes that colleges and universities use to manage and oversee their academic programs and operations. However, with the advent of digital technologies, there has been a growing trend towards the Internet+ college education management model, which integrates digital technologies into all aspects of college education management. This model includes the use of online learning platforms and tools, such as learning management systems (LMS), to deliver courses and manage student progress. It also includes the use of digital technologies for administrative tasks such as admissions, enrolment, and financial aid. However, the educational management model is subjected to the challenge of security for educational data management. Hence, this paper constructed a secure framework model of the Ethereum SDN Cloud Architecture (ESDNarc). The ESDNarc model uses the Software-defined Network (SDN) for the decentralized management of the network, secure transactions, and improved efficiency. The ESDNarch model incorporates the SDN with the cryptography scheme the secure the data. The constructed model uses the double-hashing Elliptical Curve Cryptography (DHECC) for the data stored in the Ethereum blockchain. The performance of the constructed model is evaluated with the KDD data set. Simulation analysis stated that ESDNarch significantly increases the data security in the cloud model for the attacks in the network.
The exponential growth of the Internet of Things (IoT) is being witnessed nowadays in different sectors. This makes IoT data communications more complex and harder to manage. Addressing such a challenge using a centralized model is an ineffective approach and would result in security and privacy difficulties. Technologies such as blockchain provide a potential solution to enable secure and effective management of IoT data communication in a distributed and trustless manner. In this paper, a novel lightweight blockchain-centric IoT architecture is proposed to address effective IoT data communication management. It is based on an event-driven smart contract that enables manageable and trustless IoT data exchange using a simple publish/subscribe model. To maintain system complexity and overhead at a minimum, the design of the proposed system relies on a single smart contract. All the system operations that enable effective IoT data communication among the different parties of the system are defined in the smart contract. There is no direct blockchain–IoT-device interaction, making the system more useable in wide IoT deployments incorporating IoT devices with limited computing and energy resources. A practical Ethereum-based implementation of the system was developed with the ability to simulate different IoT setups. The evaluation results demonstrated the feasibility and effectiveness of the proposed architecture. Considering varying-scale and varying-density experimental setups, reliable and secure data communications were achieved with little latency and resource consumption.
More and more millennials are interested in investing in crypto assets like Bitcoin and Ethereum. However, there is still uncertainty and hesitation in making this investment. This study aims to determine the effect of herding behavior on the millennial generation's intention to invest in crypto assets. This research was conducted in Indonesia with the respondents being the millennial generation who adopted crypto assets. The population in this study is the millennial generation of crypto asset adopters throughout Indonesia which continues to change every time, so the number is unknown. The sampling technique was carried out by purposive sampling with a sample of 220 respondents. Data was collected by distributing questionnaires via google form. The analysis used is SEM-PLS. The results of this study indicate that herding on social media environment has a positive and significant effect on behavioral intention. Herding on social media environment has a positive and significant effect on financial literacy. Herding on social media environment has a positive and significant effect on E-trust. Financial literacy has a positive and significant effect on behavioral intention. E-trust has no effect on behavioral intention. Ethical concern is able to moderate the influence of herding on social media environment on behavioral intention.
Blockchain is a promising technology that is quickly gaining traction in the realm of security that is regulated by both governmental and commercial organizations. Donors are unable to know whether their donations are being used effectively due to a complete lack of transparency in donation-related transactions, which has prompted many to stop believing in charities. The immutability, traceability, and reliability properties of blockchain technology make it a viable solution for enhancing efficiency and transparency for charity. This research work is based on the Ethereum Blockchain, the decentralized donation tracking system that will permit transparent accountability, openness, and direct communication with the intended targets. The blockchain network would be made up of well-known, reliable, and esteemed companies.
Farman Ullah Khan, Faridoon Khan, Parvez Ahmed Shaikh
Abstract The study aims at forecasting the return volatility of the cryptocurrencies using several machine learning algorithms, like neural network autoregressive (NNETAR), cubic smoothing spline (CSS), and group method of data handling neural network (GMDH-NN) algorithm. The data used in this study is spanning from April 14, 2017, to October 30, 2020, covering 1296 observations. We predict the volatility of four cryptocurrencies, namely Bitcoin, Ethereum, XRP, and Tether, and compare their predictive power in terms of forecasting accuracy. The predictive capabilities of CSS, NNETAR, and GMDH-NN are compared and evaluated by mean absolute error (MAE) and root-mean-square error (RMSE). Regarding the return volatility of Bitcoin and XRP markets, the forecasted results remarkably suggest that in contrast to rival approaches, the CSS can be an effective model to boost the predicting accuracy in the sense that it has the lowest forecast errors. Considering the Ethereum markets’ volatility, the MAE and RMSE associated with NNETAR are smaller than the MAE and RMSE of CSS and GMDH-NN algorithm, which ensures the effectiveness of NNETAR as compared to competing approaches. Similarly, in case of Tether markets’ volatility, the corresponding MAE and RMSE reveal that the GMDH-NN algorithm is an efficient technique to enhance the forecasting performance. We notice that no single tool performed uniformly for all cryptocurrency markets. The policymakers can adopt the model for forecasting cryptocurrency volatility accordingly.
Ring signcryption with no group administrator satisfies the decentralization and blockchain anonymity. In this article, we construct new lattice-based ring signcryption scheme suitable for consortium blockchain (CB-LRSCS), in which the smart contract controls the process of signcryption and unsigncryption to make the system be fair and reliable. CB-LRSCS can protect the user privacy by reducing the connection between blockchain and user information, and it satisfies the reliability in ethereum environment. CB-LRSCS also has the characteristics of high efficiency, anti-quantum, anti-forgery, confidentiality and unconditional anonymity, and it can be applied in the electronic finance system.
The COVID-19 pandemic has resulted in increased cross-sector cyber-attacks. Passive and reactive cybersecurity techniques relying solely on technology are insufficient to combat sophisticated attacks, necessitating proactive and collaborative security measures to minimize attacks. Cybersecurity Information Sharing (CIS) enhances security via proactive and collaborative cybersecurity information exchange, but its implementation via cloud services faces threats from man in the middle (MITM) and distributed denial of service (DDoS) attacks, as well as a vulnerability in cloud storage involving centralized data control. These threats and vulnerabilities result in a lack of user confidence in the confidentiality, integrity, and availability of information. This paper proposes Secure Cybersecurity Information Sharing (SCIS) to secure Cybersecurity Information in sectoral organizations using the private interplanetary file system (IPFS) network and the private Ethereum Blockchain network. Private Ethereum Blockchain enables secure and transparent transaction logging, while Private IPFS network provides decentralized storage, addressing vulnerabilities in centralized storage systems. The outcomes of the tests reveal that the suggested SCIS system offers cybersecurity information availability, confidentiality, and integrity. SCIS provides a high level of security to protect cybersecurity information exchanged between sectoral organizations using the Private Ethereum Blockchain network and the Private IPFS network so that organizations can safely share and utilize information.
As blockchain technology becomes more and more popular, a typical financial scam, the Ponzi scheme, has also emerged in the blockchain platform Ethereum. This Ponzi scheme deployed through smart contracts, also known as the smart Ponzi scheme, has caused a lot of economic losses and negative impacts. Existing methods for detecting smart Ponzi schemes on Ethereum mainly rely on bytecode features, opcode features, account features, and transaction behavior features of smart contracts, which are unable to truly characterize the behavioral features of Ponzi schemes, and thus generally perform poorly in terms of detection accuracy and false alarm rates. In this paper, we propose SourceP, a method to detect smart Ponzi schemes on the Ethereum platform using pre-trained models and data flow, which only requires using the source code of smart contracts as features. SourceP reduces the difficulty of data acquisition and feature extraction of existing detection methods. Specifically, we first convert the source code of a smart contract into a data flow graph and then introduce a pre-trained model based on learning code representations to build a classification model to identify Ponzi schemes in smart contracts. The experimental results show that SourceP achieves 87.2% recall and 90.7% F-score for detecting smart Ponzi schemes within Ethereum's smart contract dataset, outperforming state-of-the-art methods in terms of performance and sustainability. We also demonstrate through additional experiments that pre-trained models and data flow play an important contribution to SourceP, as well as proving that SourceP has a good generalization ability.
Afees A. Salisu, Ahamuefula E. Ogbonna, Tirimisiyu F. Oloko
This study examines the effect of pandemic-induced uncertainty on cryptocoins (Bitcoin, Ethereum and Ripple). It employs the Westerlund and Narayan (2012, 2015) predictive model to examine the predictability of pandemic-induced uncertainty and our model's forecast performance. We examine the role of asymmetry in uncertainty and the sensitivity of our results to the recently-developed Salisu and Akanni (2020) Global Fear Index. Cryptocoins act as a hedge against uncertainty due to pandemics, albeit with reduced hedging effectiveness in the COVID-19 period. Accounting for asymmetry improves predictability and model forecast performance. Our results may be sensitive to the choice of measure of pandemic-induced uncertainty.