The Proof-of-Work algorithm that underlies Bitcoin, Ethereum w , 1 and many other cryptocurrencies is well known for its energy-intensive requirements. The Proof-of-Stake algorithm that underlies Ethereum and various other cryptocurrencies is less impactful environmentally, but it has a second, looming issue: the problem of wealth inequality. We have developed an alternative to Proof-of-Work and Proof-of-Stake, called Proof-by-Location, that has the potential to address both of these issues. This article describes Proof-by-Location and a financial platform called Xylem that is based on it. This platform seeks to distribute transaction fees to billions of cryptocurrency “Notaries” around the world (essentially, anyone with a smartphone), who work together to establish a distributed consensus about financial transactions. In this article, we demonstrate that this platform can scale to more than 3.9 trillion transactions per year (more than triple the number of digital payments per year currently occurring). We show a reduction of electricity usage per transaction of 99.9999914% compared to Bitcoin, 99.999905% compared to Ethereum w , 99.83% compared to Ethereum, and 95.9% compared to the Visa financial services company. We demonstrate that this platform would have a redistributive rather than consolidatory effect on wealth compared to any of these platforms, leading to a source of income for more than 1 billion people around the world, including more than 110 million in the bottom 10th to 20th percentile by income, with income for that group equivalent to 8.8 million full-time jobs. Finally, this currency provides a positive, non-compulsory mechanism for shaping human habitation patterns in ways that can slow global biodiversity loss and enable ecological restoration. Using Xylem as a global financial infrastructure could lead to significantly better social and environmental outcomes than existing financial platforms. 2
There have been several studies into measuring the level of decentralization in Ethereum through applying various indices to indicate the relative dominance of entities in different domains in the ecosystem. However, these indices do not capture any correlation between those different entities, that could potentially make them the subject of external coercion, or covert collusion. We propose an index that measures the relative dominance of entities based on the application of correlation factors. We posit that this approach produces a more nuanced and accurate index of decentralization.
Bitcoin'in 2009 yılında ortaya çıkmasıyla birlikte, birçok sektör üzerindeki etkileri gözlemlenmiştir. Ancak, kripto para piyasalarındaki yüksek volatilite ve merkezi bir kontrol olmaması, kripto paraların geleceği konusunda belirsizlik yaratmaktadır. Bu anlamda, finansal sektörlerin dinamik yapısı gereği diğer sektörlerden daha hızlı etkilendikleri doğal olarak kabul edilmektedir. Bu araştırmanın temel amacı, Bitcoin, Ethereum, Litecoin ve Ripple gibi dört kripto para biriminin yatırım aracı olarak potansiyelini değerlendirmektir. Bu amaç doğrultusunda, 1 Ocak 2018 - 1 Ocak 2023 tarihleri arasında, seçili kripto para birimlerinin getiri oranlarının volatilite özellikleri modellenmeye çalışılmıştır. Otoregresif koşullu değişen varyans modelleri (Autoregressive conditional heteroskedasticity - ARCH) analizi kullanılarak yapılan çalışmada, modelin volatilite tahmininin anlamlı sonuçlar vermesi üzerine VAR analizi ve Granger nedensellik ilişkileri eklenerek desteklenmiştir. Bu testlerin sonucunda kripto para birimlerinin risk profili incelenmiş ve gelecekteki fiyat hareketlerine ilişkin bir tahmin sağlanması amaçlanmıştır. Bu şekilde, kripto para birimlerinin potansiyel bir yatırım aracı olarak değerlendirilmesi konusunda tespitler yapılarak literatüre katkıda bulunulmuştur. Bu bağlamda, serilerde ARCH etkisi gözlemlenmiştir. Yapılan VAR ve Granger Nedensellik testleri sonucunda, Bitcoin'deki bir değişikliğin diğer altcoin'leri önemli ölçüde etkilediği ancak Ripple'da anlamlı bir etkinin olmadığı sonucuna varılmıştır.
Software Development based on Scrum Agile in a distributed development environment plays a pivotal role in the contemporary software industry by facilitating software development across geographic boundaries. However, in the past different frameworks utilized to address the challenges like communication and collaboration in scrum agile distributed software development (SADSD) were notably inadequate in transparency, security, traceability, geographically dispersed location work agreements, geographically dispersed teamwork effectiveness, and trust. These deficiencies frequently resulted in delays in software development and deployment, customer dissatisfaction, canceled agreements, project failures, and disputes over payments between customers and development teams. To address these challenges of SADSD, this paper proposes a new framework called ChainAgile, which leverages blockchain technology. ChainAgile employs a private Ethereum blockchain to facilitate the execution of smart contracts. These smart contracts cover a range of functions, including acceptance testing, secure payments, requirement verification, task prioritization, sprint backlog, user story design and development and payments with the automated distribution of payments via digital wallets to development teams. Moreover, in the ChainAgile framework, smart contracts also play a pivotal role in automatically imposing penalties on customers for making late payments or for no payments and penalties on developers for completing the tasks that exceed their deadlines. Furthermore, ChainAgile effectively addresses the scalability limitations intrinsic in blockchain technology by incorporating the Interplanetary File System (IPFS) is used for storage solutions as an off-chain mechanism. The experimental results conclusively show that this innovative approach substantially improves transparency, traceability, coordination, communication, security, and trust for both customers and developers engaged in scrum agile distributed software development (SADSD).
Cryptocurrency, a digital currency managed by decentralized networks, has gained immense popularity since the inception of Bitcoin. These digital assets, often characterized by extreme price volatility, have generated substantial interest from investors. Traditional financial models struggle to account for the unique dynamics and complexities of cryptocurrencies, prompting the adoption of deep learning techniques. This study investigates the use of Long Short-Term Memory (LSTM), Neural Networks, and Deep Learning (CNN) in predicting cryptocurrency prices. These deep learning models leverage various data sources, such as technical indicators and sentiment analysis, to gain a comprehensive understanding of cryptocurrency markets. The research evaluates the performance of these models using Root Mean Squared Error (RMSE) as the primary metric. The results demonstrate that the hybrid model, combining LSTM, Neural Networks, and Deep Learning, exhibits the highest predictive accuracy across multiple cryptocurrencies, including Bitcoin (BTC), Ethereum (ETH), and Binance Coin (BNB). However, challenges persist, such as model adaptability to unforeseen market events and data noise. Future developments may involve incorporating external factors and interdisciplinary collaboration to create more holistic valuation models. Despite these challenges, the study underscores the potential of hybrid deep learning models in enhancing cryptocurrency valuation accuracy and their relevance in risk management strategies for investors and traders.
Ethereum's current Gasper consensus mechanism, which combines the Latest Message Driven Greediest Heaviest Observed SubTree (LMD-GHOST) fork choice rule with the probabilistic Casper the Friendly Finality Gadget (FFG) finality overlay, finalizes transactions in 64 to 95 blocks, an approximate 15-minute delay. This finalization latency impacts user experience and exposes the network to short-term chain reorganization risks, potentially enabling transaction censorship or frontrunning by validators without severe penalties. As the ecosystem pursues a rollup-centric roadmap to scale Ethereum into a secure global settlement layer, faster finality allows cross-layer and inter-rollup communication with greater immediacy, reducing capital inefficiencies. Single slot finality (SSF), wherein transactions are finalized within the same slot they are proposed, promises to advance the Ethereum protocol and enable better user experiences by enabling near-instant economic finality. This thesis systematically studies distributed consensus protocols through propose-vote-merge, PBFT-inspired, and graded agreement families - scrutinizing their capacities to enhance or replace LMD-GHOST. The analysis delves into the intricate tradeoffs between safety, liveness, and finality, shedding light on the challenges and opportunities in designing an optimal consensus protocol for Ethereum. It also explores different design decisions and mechanisms by which single slot or fast finality can be enabled, including cumulative finality, subsampling, and application-layer fast finality. Furthermore, this work introduces SSF-enabled and streamlined fast finality constructions based on a single-vote total order broadcast protocol. The insights and recommendations in this thesis provide a solid foundation for the Ethereum community to make informed decisions regarding the future direction of the protocol's consensus.
Sulemana Awal, Diyawu Mumin, Arnold Mashud Abukari, Abukari Aziz Danaa · 5 authors
Online services currently rely heavily on centralized authentication methods to manage user identification and authentication. However, these methods are vulnerable to account hacking, which can compromise user data and lead to attacks. A potential solution to this issue is the use of distributed ledger technology, such as blockchain, to decentralize credential ownership and provide a secure, immutable platform for verifying user identity. This paper aims to analyze the drawbacks of centralized authentication systems and propose an alternative that uses blockchain technology for authentication, ensuring robustness, transparency, and security. The proposed system is tested on web applications using the Ethereum testnet and an authentication provider (backend server).
Abstract Blockchain infrastructures have emerged as a disruptive technology and have led to the realization of cryptocurrencies (peer‐to‐peer payment systems) and smart contracts. They can have a wide range of application areas in e‐Science due to their open, public nature and global accessability in a trustless manner. We propose and implement a smart contract called eBlocBroker, which is an autonomous blockchain‐based middleware system for volunteer computing and providing data resources for e‐Science. The eBlocBroker infrastructure connects requesters who need to combine applications (jobs) with datasets and run them via an Ethereum‐based private blockchain network (Bloxberg) on providers that utilize computational and data resources on clouds or home servers. It uses cloud storage, such as B2DROP, IPFS, or Google Drive, to store and transfer data between requesters and providers. Each provider utilizes the Slurm workload manager to execute jobs submitted through eBlocBroker. In this paper, we demonstrate how an autonomous organization programmed as a smart contract can be used to deploy a marketplace that supports data and computation‐intensive research projects. We propose a cost model implemented as a function in the smart contract which calculates and records computation and dataset usage costs. We develop a Python‐based system to communicate with eBlocBroker and orchestrate jobs' execution on the provider's end. We present eBlocBroker's features, infrastructure, implementation, algorithms and experimental results.
Ateeq Ur Rehman, Nargis Tariq, Mian Ahmad Jan, Fazlullah Khan · 6 authors
In recent years, the healthcare industry has undergone a digital transformation, making patient data publicly available and accessible. Healthcare units make a portion of the data public while keeping the rest private, necessitating various mechanisms for security and privacy. Blockchain technology has been widely adopted in the healthcare sector to secure data transactions. However, public blockchains face challenges in scalability and privacy, whereas private blockchains struggle with centralization, interoperability, and complexity. To address these challenges, we propose an Internet of Medical Things (IoMT)-based hybrid blockchain architecture. The proposed architecture combines the decentralized Ethereum and the centralized Hyperledger Fabric blockchain (Eth-Fab) using SQLite to leverage Ethereum smart contracts with the Hyperledger permission model. Moreover, we introduce access control strategies to enhance patient data authentication and authorization. We have employed machine learning algorithms to assist healthcare practitioners in accurately detecting diseases and making time-efficient decisions. Additionally, we modeled the proposed architecture using the M/M/1 queuing model and derived closed-form expressions for latency, throughput, and server utilization. The validity of these expressions was verified through Monte Carlo simulations. The results demonstrate that higher service times (block generation) yield better outcomes in terms of latency, throughput, and utilization, regardless of the arrival time, i.e., transactions in the mining pool.
Currently, the relevance of using crypto assets is growing rapidly. In recent years, cryptocurrencytrading has become one of the most discussed topics in the world of finance and investment.Cryptocurrencies such as Bitcoin, Ethereum, attract the attention of millions of people due to their innovativeness,high profit potential, and decentralization possibilities. The blockchain technology, on whichcryptocurrencies are based, is one of the most innovative and promising technologies in the market. Studyingcryptocurrency trading helps understand how private investors and companies can use blockchaintechnologies for investment and business development. One of the main reasons for the popularity ofcryptocurrency trading is its high level of volatility. The cryptocurrency exchange rate can change quickly,providing opportunities for profit. This article focuses on exploring the use of predictive analytics fordecision-making in decentralized systems using cryptocurrency trading on centralized and decentralizedexchanges as an example. The research conducted in this work aims to investigate decentralized and centralizedsystems to further develop decision support systems. A general description and operation schemesof decentralized and centralized dynamic systems are provided using cryptocurrency exchanges as a researchexample. This scientific article examines the typical structure of centralized and decentralizedcryptocurrency exchanges, analyzing the fundamental components and principles of their functioning.The article discusses the internal organization of the exchange, including the system for storing digital assets, transaction execution mechanisms, security provisions, and risk management. It also examines theinteraction between the exchange and market participants, as well as regulatory bodies. Furthermore, thisscientific article explores the rules and principles of operation for traders and market makers on centralizedand decentralized cryptocurrency exchanges. It covers the main strategies and tactics used by marketparticipants to ensure liquidity and optimize trading operations. The article compares the trading approacheson different types of cryptocurrency exchanges considering their specific features and impact oncryptocurrency price dynamics. The presented results can contribute to a deeper understanding ofcryptocurrency trading processes and optimize decision-making strategies for investors and traders in thecrypto asset market.
Reentrancy vulnerability as one of the most notorious vulnerabilities, has been a prominent topic in smart contract security research. Research shows that existing vulnerability detection presents a range of challenges, especially as smart contracts continue to increase in complexity. Existing tools perform poorly in terms of efficiency and successful detection rates for vulnerabilities in complex contracts. To effectively detect reentrancy vulnerabilities in contracts with complex logic, we propose a tool named SliSE. SliSE’s detection process consists of two stages: Warning Search and Symbolic Execution Verification . In Stage I, SliSE utilizes program slicing to analyze the Inter-contract Program Dependency Graph (I-PDG) of the contract, and collects suspicious vulnerability information as warnings. In Stage II, symbolic execution is employed to verify the reachability of these warnings, thereby enhancing vulnerability detection accuracy. SliSE obtained the best performance compared with eight state-of-the-art detection tools. It achieved an F1 score of 78.65%, surpassing the highest score recorded by an existing tool of 9.26%. Additionally, it attained a recall rate exceeding 90% for detection of contracts on Ethereum. Overall, SliSE provides a robust and efficient method for detection of Reentrancy vulnerabilities for complex contracts.
Ayesha Hakim, Sundus Shafique, Mubashir Mehdi, Irfan Ahmad Baig
Globally, the mango industry is one of the largest industrial sectors – also considered the backbone industry of the country’s agriculture sector. This sector mobilizes key industrial activities of many economies, such as agriculture, production, handling, storage, logistics, certification, and packing of a variety of mangoes (e.g., with over 1,500 varieties, of which at least 30 are grown commercially in Pakistan). From local, regional, and national, to international levels, many businesses in this sector are involved in extensive mango supply networks fulfilling the demands of many consumers and markets (e.g., B2B, B2C, etc.) locally worldwide. Currently, 43% of total farmers in Pakistan are smallholder farmers, as they possess less than 2.6 hectares of land. Intermediaries dominate the entire supply chain in Pakistan, due to which small to average farmers face several challenges. This can be avoided by developing a user-friendly system to link farmers directly to the market or consumers. The proposed system identifies the gaps in the process model of Pakistan’s mango supply chain system. It creates a platform to link farmers directly to the market or consumers through a seamless online system using blockchain technology for performing reliable transactions using smart contracts. The proposed system is implemented through Ethereum, a permissioned blockchain network using Smart Contracts. It is a distributed ledger accessible to participants of the supply chain with permission to ensure the trust and authenticity of the information. By using this system, the farmers will attain increased profit through direct access to retailers, consumers, and the international market.
The wide application of smart contracts allows industry companies to implement some complex distributed collaborative businesses, which involve the calculation of complex functions, such as matrix operations. However, complex functions such as matrix operations are difficult to implement on Ethereum Virtual Machine (EVM)-based smart contract platforms due to their distributed security environment limitations. Existing off-chain methods often result in a significant reduction in contract execution efficiency, thus a platform software development kit interface implementation method has become a feasible way to reduce overheads, but this method cannot verify operation correctness and may leak sensitive user data. To solve the above problems, we propose a verifiable EVM-based smart contract cross-language implementation scheme for complex operations, especially matrix operations, which can guarantee operation correctness and user privacy while ensuring computational efficiency. In this scheme, a verifiable interaction process is designed to verify the computation process and results, and a matrix blinding technology is introduced to protect sensitive user data in the calculation process. The security analysis and performance tests show that the proposed scheme can satisfy the correctness and privacy of the cross-language implementation of smart contracts at a small additional efficiency cost.
The scalability limitations of public blockchains have hindered their widespread adoption in real-world applications. While the Ethereum community is pushing forward in zk-rollup (zero-knowledge rollup) solutions, such as introducing the ``blob transaction'' in EIP-4844, Layer 2 networks encounter a data availability problem: storing transactions completely off-chain poses a risk of data loss, particularly when Layer 2 nodes are untrusted. Additionally, building Layer 2 blocks requires significant computational power, compromising the decentralization aspect of Layer 2 networks. This paper introduces new techniques to address the data availability and decentralization challenges in Layer 2 networks. To ensure data availability, we introduce the concept of ``proof of download'', which ensures that Layer 2 nodes cannot aggregate transactions without downloading historical data. Additionally, we design a ``proof of storage'' scheme that punishes nodes who maliciously delete historical data. For decentralization, we introduce a new role separation for Layer 2, allowing nodes with limited hardware to participate. To further avoid collusion among Layer 2 nodes, we design a ``proof of luck'' scheme, which also provides robust protection against maximal extractable value (MEV) attacks. Experimental results show our techniques not only ensure data availability but also improve overall network efficiency, which implies the practicality and potential of our techniques for real-world implementation.
Kainat Ansar, Mansoor Ahmed, Saif Ur Rehman Malik, Markus Helfert · 5 authors
Context Data breaches caused by insiders are on the rise, both in terms of frequency and financial impact on organizations. Insider threat originates from within the targeted organization and users with authorized access to an organization’s network, applications, or databases commit insider attacks. Motivation Insider attacks are difficult to detect because an attacker with administrator capabilities can change logs and login records to destroy the evidence of the attack. Moreover, when such a harmful insider attack goes undetected for months, it can do a lot of damage. Such data breaches may significantly impact the affected data owner’s life. Developing a system for rapidly detecting data breaches is still critical and challenging. General Data Protection Regulation (GDPR) has defined the procedures and policies to mitigate the problems of data protection. Therefore, under the GDPR implementation, the data controller must notify the data protection authority when a data breach has occurred. Problem Statement Existing data breach detection mechanisms rely on a reliable third party. Because of the presence of a third party, such systems are not trustworthy, transparent, secure, immutable, and GDPR-compliant. Contributions To overcome these issues, this study proposed a GDPR-compliant data breach detection system by leveraging the benefits of blockchain technology. Smart contracts are written in Solidity and deployed on a local Ethereum test network to implement the solution. The proposed system can generate alert notifications against every data breach. Results We tested and deployed our proposed system, and the findings indicate that it can accomplish the insider threat mitigation objective. Furthermore, the GDPR compliance analysis of our system was also evaluated to make sure that it complies with the GDPR principles (such as right to be forgotten, access control, conditions for consent, and breach notifications). The conducted analysis has confirmed that the proposed system offers capabilities to comply with the GDPR from an application standpoint.
The office attendance system has shifted from using physical forms to digital inputs to minimize data errors and data loss when taking attendance. Unfortunately, digital systems generally still use traditional databases where the admin's role is crucial, and there is potential for fraud (e.g., admitting attendance of a non-attending person or manipulating a targeted person’s log due to personal grudges, competition, or other reasons) if the admin is dishonest. In this paper, we propose Absenin, a blockchain-based office attendance system, which replaces the role of traditional databases with blockchain and smart contracts to make it secure from malicious admins and fair for other participants. We create an Attendance Smart Contract that will run on the Ethereum blockchain. Admins and employees will interact with this smart contract to carry out attendance system operations. Absenin is also designed to have real-time attendance data, but the attendance machine does not need to be connected to the Internet, which is a unique feature of our system that no previous works have attempted. Despite using blockchain and smart contracts, our evaluation results show that Absenin is able to produce relatively small processing delays, and gas usage on the blockchain is still far below the gas limit of the Ethereum mainnet. Therefore, we can assure that the system is feasible and can be applied to organizations with a scale of thousands, tens, or hundreds of thousands of employees.
The core of many cryptocurrencies is the decentralised validation network operating on proof-of-work technology. In these systems, validation is done by so-called miners who can digitally sign blocks once they solve a computationally-hard problem. Conventional wisdom generally considers this protocol as secure and stable as miners are incentivised to follow the behaviour of the majority. However, whether some strategic mining behaviours occur in practice is still a major concern. In this paper we target this question by focusing on a security threat: a selfish mining attack in which malicious miners deviate from protocol by not immediately revealing their newly mined blocks. We propose a statistical test to analyse each miner's behaviour in five popular cryptocurrencies: Bitcoin, Litecoin, Monacoin, Ethereum and Bitcoin Cash. Our method is based on the realisation that selfish mining behaviour will cause identifiable anomalies in the statistics of miner's successive blocks discovery. Secondly, we apply heuristics-based address clustering to improve the detectability of this kind of behaviour. We find a marked presence of abnormal miners in Monacoin and Bitcoin Cash, and, to a lesser extent, in Ethereum. Finally, we extend our method to detect coordinated selfish mining attacks, finding mining cartels in Monacoin where miners might secretly share information about newly mined blocks in advance. Our analysis contributes to the research on security in cryptocurrency systems by providing the first empirical evidence that the aforementioned strategic mining behaviours do take place in practice.
Open access
Blockchain Technology Applications and Security
Spam and Phishing Detection
Advanced Steganography and Watermarking Techniques
M. S. Anbarasi, P. Barath, Y. Bharath, Arun Kumar J. · 5 authors
In the realm of cloud server operations, where the sheer volume of daily transactions is immense, safeguarding data security is paramount. One of the significant challenges faced is the verification of transaction logs, as attackers may attempt to tamper with them. The current system, utilizing Proof of Work (PoW) for blockchain, falls short by lacking robust data encryption, thereby exposing a critical vulnerability. This proposed paper introduces an innovative solution by integrating the more secure and energy-efficient Proof of Stake (PoS) algorithm with Blowfish encryption. The combination of PoS and Blowfish addresses the identified weaknesses effectively. PoS introduces a novel approach by relying on validators who have a stake in the network, creating a powerful deterrent against log tampering. This not only enhances the integrity of the transaction logs but also reduces the risk of malicious activities. Additionally, the incorporation of Blowfish encryption ensures the confidentiality of log data, providing an extra layer of protection. Even if logs are accessed illicitly, the encryption prevents unauthorized individuals from deciphering sensitive information. Furthermore, the implementation of a smart contract for user registration adds another dimension to security, creating a comprehensive solution to fortify data security on Cloud servers. The proposed approach offers a promising solution to the critical cybersecurity challenge faced by cloud servers. By combining the security features of PoS and Blowfish encryption, along with the strategic use of smart contracts, the solution not only deters tampering but also safeguards sensitive information. This holistic approach contributes significantly to reinforcing the data security infrastructure of cloud servers in the face of evolving cyber threats.
P. Maragathavalli, Aravindhar RS, R Keerthana, M. Harini · 5 authors
Cybercrime gives challenges to law enforcement agencies to secure digital evidence and maintain its integrity. Blockchain known for its decentralized and immutable nature, provides a secure ledger to record digital evidence transactions restricting unauthorized access. This project proposes a framework for digital forensic evidence management, contributing to the enhancement of security and reliability in digital forensic practices through the utilization of Ethereum Blockchain technology and Advanced Encryption Standard (AES) encryption. Through a systematic review, various studies, methodologies, and implementations employing Blockchain to safeguard digital evidence are explored. Blockchain, known for its decentralized and immutable nature, provides a secure ledger to record digital evidence transactions, restricting unauthorized access. Advanced Encryption Standard (AES) algorithm ensures that the data stored on the blockchain remains tamper-resistant and secure. In the blockchain ecosystem, Proof of Stake (POS) plays a critical role by facilitating transaction validation and block creation. It distinguishes itself by selecting validators based on the amount of cryptocurrency they 'stake' or pledge as collateral, offering an energy-efficient and environmentally sustainable alternative to the traditional method.
Electronic commerce and finance are progressively supporting and including decentralized, shared and public ledgers such as the blockchain. This is reshaping traditional commercial activities by advancing them towards Decentralized Finance (DeFi) and Commerce 3.0, thereby supporting the latter’s potential to outpace the hurdles of central authority controllers and lawgivers. The quantity and entropy of the information that must be sought and managed to become active participants in such a relentlessly evolving scenario are increasing at a steady pace. For example, that information comprises asset or service description, general rules of the game, and specific technologies involved for decentralization. Moreover, the relevant information ought to be shared among innumerable and heterogeneous stakeholders, such as producers, buyers, digital identity providers, valuation services, and shipment services, to just name a few. A clear semantic representation of such a complex and multifaceted blockchain-based e-Commerce ecosystem would contribute dramatically to make it more usable, namely more automatically accessible to virtually anyone wanting to play the role of a stakeholder, thereby reducing programmers’ effort. However, we feel that reaching that goal still requires substantial effort in the tailoring of Semantic Web technologies, hence this article sets out on such a route and advances a stack of OWL 2 ontologies for the semantic description of decentralized e-commerce. The stack includes a number of relevant features, ranging from the applicable stakeholders through the supply chain of the offerings for an asset, up to the Ethereum blockchain, its tokens and smart contracts. Ontologies are defined by taking a behaviouristic approach to represent the various participants as agents in terms of their actions, inspired by the Theory of Agents and the related mentalistic notions. The stack is validated through appropriate metrics and SPARQL queries implementing suitable competency questions, then demonstrated through the representation of a real world use case, namely, the iExec marketplace.
The blockchain technology can become a solution in data privacy and protection, being considered a public and decentralized database, in which the identity of a user is masked in the form of an address. Based on this technology, several decentralized protocols such as Bitcoin or Ethereum have been created, with the help of which decentralized applications can be created. In this article, we examine how these technologies can be used to ensure the transparency of a software application, but also the privacy and protection of user data. Other facilities like Non-Fungible Token - NFT and Smart Contract are used. The paper proposes the design and the implementation (including the source code) of a web platform for education / courses incorporating blockchain technology. The results and conclusions are showed. Finally, the contributions of the paper, the limitations and future works are also highlighted.
Ethereum 2.0 is a major upgrade to improve its scalability, throughput, and security. In this version, RANDAO is the scheme to randomly select the users who propose, confirm blocks, and get rewards. However, a vulnerability, referred to as the `Last Revealer Attack' (LRA), compromises the randomness of this scheme by introducing bias to the Random Number Generator (RNG) process. This vulnerability is first clarified again in this study. After that, we propose a Shamir's Secret Sharing (SSS)-based RANDAO scheme to mitigate the LRA. Through our analysis, the proposed method can prevent the LRA under favorable network conditions.
This paper studies the market structure impact of cheaper and faster chains on the Uniswap v3 Protocol. The Uniswap Protocol is the largest decentralized application on Ethereum by both gas and blockspace used, and user behaviors of the protocol are very sensitive to fluctuations in gas prices and market structure due to the economic factors of the Protocol. We focus on the chains where Uniswap v3 has the most activity, giving us the best comparison to Ethereum mainnet. Because of cheaper gas and lower block times, we find evidence that the majority of swaps get better gas-adjusted execution on these chains, liquidity providers are more capital efficient, and liquidity providers have increased fee returns from more arbitrage. We also present evidence that two second block times may be too long for optimal liquidity provider returns, compared to first come, first served. We argue that many of the current drawbacks with AMMs may be due to chain dynamics and are vastly improved with cheaper and faster transactions