Large Language Models (LLMs) empowered agents are effective across various tasks and demonstrate outstanding performance, which can be further enhanced through collaboration with multiple LLM agents. The current approaches for collaboration with multiple LLM agents are static approaches, which adopt a fixed set of agents to interact with each other. However, these approaches suffer from a significant limitation: multi-agent collaboration depends on the assumption that all participants know each other in a local closed environment, can find each other and direct communication, and will act with integrity. To address these challenges, this paper proposes DeCoAgent, a novel framework for decentralized autonomous collaboration between LLMs empowered agents based on smart contracts. This framework enables decentralized autonomous collaboration between LLM agents, allowing them to register themselves, discover the capabilities of other agents, and assign tasks on the platform. LLMs can convert natural language descriptions from human and LLM agent users into smart contract calls, enabling agents to interact with humans, the blockchain, and other agents to achieve automation. This paper implements the platform based on OpenAI and Ethereum, demonstrating the practical feasibility of this approach. The proposed framework has broader applications, including supply chain management, manufacturing, crowdsourcing, and complementing other existing multi-agent collaborations. This framework is open source on GitHub. Please visit the repository athttps://github.com/AnanKing/DeCoAgent.
Juvvala Sailaja, Kovvuri N. Bhargavi, G. L. Narasamba Vanguri, Nagireddi Suryakala · 5 authors
Crypto currencies have emerged as a popular investment option in recent years, with Ethereum being one of the most prominent ones.Accurate price prediction of Ethereum can provide valuable insights to investors and traders for making informed decisions.In this study, we utilized two time series prediction models, ARIMA (Auto Regressive Integrated Moving Average) and Facebook Prophet, to predict the price of Ethereum.This research focuses on collecting legacy price data of Ethereum from a reliable source.The data was preprocessed to handle missing values and outliers.ARIMA and Facebook Prophet models were then implemented on the preprocessed data to generate Ethereum price forecasts.The models were trained using a time period of historical data and validated using a hold-out set of data.The MSE, which measures the squared discrepancies between predicted and real Ethereum prices, was used to assess the models' performance.Lower MSE values indicate better model performance.The results revealed that Facebook Prophet outperformed ARIMA in terms of MSE, indicating superior accuracy in Ethereum price prediction.The higher accuracy of Facebook Prophet may be attributed to it's ability to handle seasonality, trend changes, and outliers, which are common characteristics of crypto currency price data.In conclusion, this study demonstrates the effectiveness of time series forecasting models, specifically ARIMA and Facebook Prophet, in predicting Ethereum prices.The findings suggest that Facebook Prophet may be a more accurate model compared to ARIMA for Ethereum price prediction, as evidenced by lower MSE values.The study provides valuable insights for investors and traders interested in utilizing forecasting models for Ethereum price prediction, and may serve as a basis for further research in this area.
Solidity is very useful language programming in modeling investment and Finance exercises blockchain technology. The book covers BA and BS, MA and MS in Risk Management, Business Administration, Financial Services, International Business and Financial Derivatives and BS in Computational Finance. Most importantly, the book includes a range of materials to help the student, the practitioners and the investors to reinforce their learning skills in cryptocurrency programming. The market will be very responsive for our book especially that a lot of international students experience problem with their English and their numerical skills. It will cover the basic needs of postgraduate students and those who are interesting in investment and tokens creation. Readers would be able to understand token contracts. Buyers would be allowed to buy tokens using Ethers. Cryptocurrency companies could raise funds by making use of initial token offering, (ITO), by selling their tokens to other investors. The market in the next five years will become very complicated and would require the use of sophisticated risk management techniques and technological solutions in order to hedge market, operational, and credit risk. Good luck in your future career as crypto developer and investment programmer in the major investment banks such as JP Morgan, Merrill Lynch, Morgan Stanley, Deutsche Bank, Goldman Sachs, and Bank of America. I would like to thank the Schweser Kaplan organization for the professional education that covers the syllabus of the Chartered Financial Institute, (CFA). Parts of the CFA examples are used to calibrate the financial models. Please e-mail me if you have any questions or if you would like to suggest investment exercises. My e-mail is guirguismichel@gmail.com
In the rapidly evolving landscape of e-HealthCare in Saudi Arabia, enhancing the security and integrity of Electronic Health Records (EHRs) is imperative. Existing systems encounter challenges stemming from centralized storage, vulner-able data integrity, susceptibility to power failures, and issues of ownership by entities other than the patients themselves. Moreover, the sharing of sensitive patient information among anonymous bodies exacerbates the vulnerability of these records. In response to these challenges, this paper advocates for the trans-formative potential of blockchain technology. Blockchain, with its decentralized and distributed architecture, offers a revolutionary approach to communication among network nodes, eliminating the need for a central authority. This paper proposes a solution that places the patient at the forefront, empowering them as the primary controller of their medical data. The research delves into the current state of e-HealthCare in Saudi Arabia, examines the challenges faced by existing EHR systems, and introduces blockchain technology, particularly Ethereum, as a viable and transformative solution. The paper details the use of Ethereum blockchain to secure and manage medical records, with a Public Key Infrastructure (PKI) applied to safeguard the confidentiality of patient information. The decentralized InterPlanetary File System (IPFS) is employed for the secure and resilient storage of encrypted medical records. Additionally, Smart contracts, integral to the Ethereum blockchain, play a central role in automating and enforcing the rules governing access to medical records. Moreover, a Web 3.0 decentralized application (DApp) is developed to provide a user-friendly interface, empowering patients to seamlessly interact with and control access to their health data. At the end, this paper presents a guiding framework for clinicians, policymakers, and academics, illustrating the trans-formative potential of blockchain and associated technologies in revolutionizing EHR management in Saudi Arabia’s healthcare systems.
Cryptocurrency is starting to be considered as an asset class for investment portfolios because of the multiple competitive advantages it has and its beneficial correlation to other asset classes. Most investors in cryptocurrency are speculators driven by market sentiment, investing according to technical analysis. There is a gap between technical analysis and fundamental analysis in the area of cryptocurrency. With the adoption of fundamental analysis the real intrinsic value of cryptocurrency can be achieved with higher returns being gained. This research aims to identify key variables and valuation metrics of Ethereum Blockchain Networks in order to predict the intrinsic value of ether through linear multiple regression. This will involve presenting a model including fundamental variables of the Ethereum Blockchain Network and market sentiment with the objective of achieving higher returns for investors of ether. There will be a focus on fundamental analysis, rather than technical analysis, of cryptocurrency because it is presume that has a greater relation to the intrinsic value of cryptocurrency. Based on the research's unsupervised method of linear regression, a price prediction model of ether with a Mean Sum Square Error of 1.1266*e^-6 and R square of 99% is devised. The results indicate that the features of the Ethereum Blockchain Network and valuation metrics have more predicting power than the market sentiment (Crix-Crypto Index). The research highlight that the most significant variable to ether are gas price per block, transactions fees and reward to miners, and focused on the utility of ether which can be of intrinsic value and have a significant impact on investment portfolios.
Ethereum 2.0 introduced several significant upgrades, one being Ethereum Improvement Proposal 1559 (EIP-1559), which changed how gas price is determined. This study examines the relationship between gas price and user activity on the Ethereum protocol following EIP-1559 sampled every minute from December 1, 2023, 00:00:00 to December 15, 2023 23:59:59. This study shows a weak positive Pearson correlation between gas price and user activity with a bidirectional Granger causality between them. In other words, an increase in gas price does not decrease user activity, and vice versa. This contrasts with an earlier study before EIP-1559, which showed a moderate to strong negative Pearson correlation between gas price and user activity, as well as an only unidirectional Granger causality from gas price to user activity. The explanation asserted in that earlier study was that when gas prices were high, users waited to submit a transaction, possibly to avoid overpaying. The shift observed in this study, where increases in gas price no longer decrease user activity, shows that EIP-1559 appears to have enhanced user confidence in gas price calculations. This in turn influences their decision-making. Specifically, users are generally more assured in continuing their transactions under the new mechanism, as can be shown from the observation that the raising in gas prices does not cause user activity to decrease. On the other hand, the new observation of Granger causality in which increases in user activity slightly increases gas price is likely a result of the new gas price formula introduced by EIP-1559, which takes into account the network congestion and caps the extent of gas price adjustments. This formula introduces a predictable link between user activity dynamics and gas prices, thereby providing greater certainty for users.
As blockchains shift from energy-hungry Proof-of-Work to capital-intensive Proof-of-Stake, they trade electricity costs for a new vulnerability: the risk of a capital run that can destabilize consensus and security. We model investors who choose between staking their coin to earn rewards or exiting to cash out, potentially triggering mass withdrawals. These "staking runs" are more likely when protocols are weak, when failure would hit coin prices hard, or when staking rewards are low. Leverage worsens things: margin calls accelerate exits and amplify run dynamics. Longer lock-up periods slow the run but may not prevent it. Previous research shows that low rewards are good for protocol security. We show they also raise the risk of a run. A run on a major Proof-of-Stake chain---like Ethereum---could destabilize the entire crypto ecosystem, threatening DeFi platforms that depend on it.
Today, educational data, controlled centrally by educational institutions and administrative units, may be vulnerable to damage caused by natural disasters, political instability, and wars. Simultaneously, challenges arise in accessing this data for educational activities within the framework of exchange programs or lifelong learning. In the literature, there are numerous blockchain-based studies focusing on storing and sharing data in various fields. While several studies exist on blockchain applications for certification, verification, and data sharing in the education sector, a fully decentralized infrastructure has not yet been presented. To address this issue, it is proposed that data control should shift to the hands of students, who are the rightful owners of the data, rather than being solely in the hands of educational institutions. In alignment with the decentralized internet vision, Web3, public blockchain networks are considered the most suitable infrastructure for this purpose. To meet this need, a framework named PublicEduChain has been introduced within the scope of this study. PublicEduChain allows students to store their data in smart contracts created on the public Ethereum network, making it possible to share this information with any educational institution and administrative units. Educational institutions can access student data stored in smart contracts on the public Ethereum network through Learning Management System (LMS) applications and can add data to these contracts. PublicEduChain ensures that data is managed under student ownership within a fully decentralized infrastructure. The practical steps in PublicEduChain, such as creating a smart contract, logging into LMSs with Ethereum IDs, and allowing LMSs to read and write data in the student contract, are explained in detail.
Decentralized finance (DeFi) offers a range of financial instruments and services that leverage the capabilities of web3 technology. Maker protocol, which enables users to obtain loans backed by cryptocurrencies, is one of them. Unlike traditional banks, Maker’s data is transparently recorded on the Ethereum blockchain. In this research paper, we focus on analyzing the lending aspect of Maker from a traditional finance perspective. To achieve this, we create a unique dataset with loan portfolios from the MakerDAO project, making it the first dataset of its kind in the DeFi field. This publicly available dataset contains essential financial characteristics related to borrowing, including balance, loss given default, annual equivalent rate, and probability of default. Additionally, we develop a specialized mathematical model tailored specifically to this project. This model allows us to estimate the probability of default by considering the presence of crypto-collateral and utilizing Brownian motion passage levels. The results of this study provide valuable insights into lending practices in DeFi projects. They also help bridge the gap between traditional finance and blockchain-based financial services.
Supply chain management (SCM), product traceability, and product quality certification are some of the initial prominent uses of blockchain technology. This is because blockchain technology is built on trust and cannot be changed. The popularity of blockchain technology is increasing as it is trustworthy and cannot be changed; hence making traceability easier for information such as where food came from, thus essential for managing the agricultural food supply chain (SC). On the contrary, suggested SCM systems premised on smart contract technology and blockchain tend to be specifically apply to production and production processes. Through qualitative research, this paper suggests framework for adoption of smart contracts based on Ethereum in the agri-food SC, with the aim to establish means to adopt blockchain for checking food quality and origins in the agri-food supply chain. Remix IDE is utilised to build and test the smart contract. The significance of the framework is realised through ensuring the traceability of product safety and quality.
Likhitha Amasala, Mahesh Datta Sai Ponnuru, P. Srideviponmalar
At present, technological systems lack a secure and transparent method for tracking goods and preventing theft in e-commerce, leading to trust issues and data vulnerabilities. There is a pressing need for a comprehensive solution that integrates Ethereum blockchain, IPFS, and advanced cryptographic techniques to address these challenges and enhance the security and transparency of transactions. This research paper presents a robust system that harnesses the Ethereum blockchain, IPFS (Interplanetary File System), and advanced cryptographic algorithms to create a secure, decentralized approach for tracking goods and preventing theft incidents. Unique identifiers and related information will be sent to the mail of the customer and same should entered by the customer for successful transaction. By assigning unique identifiers to purchased products and employing cryptographic techniques to encrypt sensitive data, our system ensures both user privacy and the creation of an immutable transaction ledger. Users can efficiently manage their purchased goods, block stolen items, and communicate with sellers through an intuitive interface. Additionally, the system provides sellers with a comprehensive transaction history, enhancing accountability and transparency within the supply chain. Through this research, we demonstrate the effectiveness of our blockchain based anti-theft measures, underpinned by Ethereum, IPFS, and cutting-edge cryptographic algorithms, in fostering secure, trustless transactions. This work highlights the transformative potential of blockchain technology and decentralized protocols in revolutionizing security and transparency across diverse sectors.
Muhamad Agil Fachrian, Parman Sukarno, Aulia Arif Wardana
Abstract This research proposes a system to store transaction records from a payment gateway based on digital payments by utilizing blockchain technology and Interplanetary File System (IPFS) as distributed storage. In digital payments, the possibility of online fraud or theft of customer data is a problem that needs to be solved. Although the solution is to use a Payment Gateway with security standards to prevent these problems, the system is still centralized and vulnerable to the possibility of system failure or data changes by irresponsible people. Blockchain furnishes a secure and unalterable record for documenting payment transactions. Conversely, IPFS presents a decentralized and immune-to-censorship approach for storing and accessing data. The usage of these technologies guarantees the secure storage of payment transaction data and related documents (such as invoices and receipts) while effectively thwarting data manipulation or censorship attempts. Therefore, this research aims to build a blockchain technology system to increase security and maintain the integrity of the data generated from the Payment Gateway. This research using distributed data storage using IPFS to save transaction from the payment gateway data. Based on the evaluation and security analysis results, implementing a blockchain technology system to store transaction records from digital-based payment gateways can improve data security and integrity. In the gas fee increase analysis, the gas fee will increase according to the total number of bytes generated when the transaction is made, where each byte will cost 12 gwei to pay the gas fee.
Krzysztof Gogol, Robin Fritsch, Malte Schlosser, Johnnatan Messias · 6 authors
This paper studies liquid staking tokens (LSTs) on automated market makers (AMMs), both theoretically and empirically. LSTs are tokenized representations of staked assets on proof-of-stake blockchains. First, we model LST-liquidity on AMMs theoretically, categorizing suitable AMM types for LST liquidity and deriving formulas for the necessary returns from trading fees to adequately compensate liquidity providers under the particular price trajectories of LSTs. For the latter, two relevant metrics are considered: (1) losses compared to holding the liquidity outside the AMM (loss-versus-holding, or "impermanent loss"), and (2) the relative profitability compared to fully staking the capital (loss-versus-staking) which is specifically tailored to the case of LST-liquidity. Next, we empirically measure these metrics for Ethereum LSTs across the most relevant AMM pools. We find that, while trading fees often compensate for impermanent loss, fully staking is more profitable for many pools, raising questions about the sustainability of the current LST liquidity allocation to AMMs.
The advent of Central Bank Digital Currencies (CBDCs) represents a significant evolution in monetary systems, enhancing transparency, efficiency, and resilience in financial transactions. This research presents a comprehensive CBDC framework that integrates centralized databases with decentralized blockchain technology, aimed at strengthening monetary oversight and tackling challenges such as money laundering and financial irregularities. By employing blockchain’s immutable ledger, the proposed system supports secure and transparent digital transactions, thereby fostering trust and accountability in the financial ecosystem. Furthermore, the framework promotes financial inclusion by offering various transaction methods, such as internet-based payments, smart cards, and offline One-Time Password (OTP) systems. This diverse approach helps users in areas with limited internet access, effectively bridging critical gaps in digital accessibility and ensuring that everyone can participate in the digital economy. Through prototype development and empirical evaluation using tools like Ethereum, Geth, and web3.js, the study explores CBDC’s potential for sustainable economic development, offering insights into practical applications and future scalability.
Dongze Li, Kejia Zhang, Shiwei Li, Gang Du · 5 authors
As decentralized finance (DeFi) grows and decentralized exchanges (DEXs) expand, the security of Ethereum smart contracts and blockchain transactions is receiving increasing scholarly attention. The ERC20 token standard has facilitated the emergence of numerous honeypot contracts, which deceive traders by allowing token purchases but blocking withdrawals. This study proposes a lightweight honeypot contract detection system integrated into the go-Ethereum client (Geth). Unlike previous work, our detector does not rely on contract interaction records or source code provided by contract creators. Instead, our approach performs static data flow analysis on contract bytecode to identify honeypot mechanisms. By focusing exclusively on the control flow of the ERC20 Transfer method, our system achieves faster detection than full-contract analysis methods, with an average processing time of 9.74 milliseconds per contract. Experiments on both known honeypot contracts and real-world token contracts demonstrate the effectiveness of our approach in detecting malicious ERC20 contracts.
Burak Öz, Danning Sui, Thomas Thiery, Florian Matthes
The MEV-Boost block auction contributes approximately 90% of all Ethereum blocks. Between October 2023 and March 2024, only three builders produced 80% of them, highlighting the concentration of power within the block builder market. To foster competition and preserve Ethereum's decentralized ethos and censorship-resistance properties, understanding the dominant players' competitive edges is essential. In this paper, we identify features that play a significant role in builders' ability to win blocks and earn profits by conducting a comprehensive empirical analysis of MEV-Boost auctions over a six-month period. We reveal that block market share positively correlates with order flow diversity, while profitability correlates with access to order flow from Exclusive Providers, such as integrated searchers and external providers with exclusivity deals. Additionally, we show a positive correlation between market share and profit margin among the top ten builders, with features such as exclusive signal, non-atomic arbitrages, and Telegram bot flow strongly correlating with both metrics. This highlights a "chicken-and-egg" problem where builders need differentiated order flow to profit, but only receive such flow if they have a significant market share. Overall, this work provides an in-depth analysis of the key features driving the builder market towards centralization and offers valuable insights for designing further iterations of Ethereum block auctions, preserving Ethereum's censorship resistance properties.
Krzysztof Gogol, Johnnatan Messias, Deborah Miori, Claudio J. Tessone · 5 authors
Arbitrage can arise from the simultaneous purchase and sale of the same asset in different markets in order to profit from a difference in its price. This work systematically reviews arbitrage opportunities between Automated Market Makers (AMMs) on Ethereum ZK rollups, and Centralised Exchanges (CEXs). First, we propose a theoretical framework to measure such arbitrage opportunities and derive a formula for the related Maximal Arbitrage Value (MAV) that accounts for both price divergences and liquidity available in the trading venues. Then, we empirically measure the historical MAV available between SyncSwap, an AMM on zkSync Era, and Binance, and investigate how quickly misalignments in price are corrected against explicit and implicit market costs. Overall, the cumulative MAV from July to September 2023 on the USDC-ETH SyncSwap pool amounts to $104.96k (0.24% of trading volume).
Daniele Granata, Massimiliano Rak, Paolo Palmiero, Adele Pastena
Despite the growing role of information and communication technology (ICT) in public administration, paper ballots still dominate elections, especially in Italy. Electronic voting has had limited success worldwide, largely due to security and manipulation concerns. The COVID-19 pandemic has reignited interest in remote e-voting for safe participation while social distancing, though security remains a critical issue. Embracing electronic voting is essential to safeguard rights, improve resource efficiency, and promote digital citizenship. Accordingly, to address security concerns in e-voting, this research emphasizes the importance of security and legal measures. The study is based on ISO15408 (Common Criteria) certification process, a framework for independent security evaluations. The paper proposes a methodology that combines legal and technical requirements for e-voting security assessments, focusing on BPMN processes to model scenarios. The methodology has been applied to a common Ethereum smart contract, focusing on the e-voting process. A detailed analysis of a Solidity e-voting smart contract reveals its vulnerabilities and limitations. The research also produces a BPMN representation of an e-voting scenario, aligning logical behaviour with smart contract implementation. The aim is to bridge the gap between legal and technical aspects of e-voting, enhancing security and transparency.