Mikel Cortes-Goicoechea, Csaba Király, Dmitriy Ryajov, José L. Muñoz · 5 authors
Scalability in blockchain remains a significant challenge, especially when prioritizing decentralization and security. The Ethereum community has proposed comprehensive data-sharding techniques to overcome storage, computational, and network processing limitations. In this context, the propagation and availability of large blocks become the subject of research to achieve scalable data-sharding. This paper provides insights after exploring the usage of a Kademlia-based Distributed Hash Table (DHT) to enable Data Availability Sampling (DAS) in Ethereum. It presents a DAS-DHT simulator to study this problem and validates the results of the simulator with experiments in a real DHT network, InterPlanetary File System (IPFS). Our results help us understand what parts of DAS can be achieved based on existing Kademlia DHT solutions and which ones cannot. We discuss the limitations of DHT solutions and discuss other alternatives.
Sangtian Guan, Juanjuan Li, Wenwen Ding, Fei–Yue Wang
In response to concerns over the centralization tendency in the decentralized autonomous organizations (DAOs), TRUE autonomous organizations and operations (TAOs or TRUE DAOs) have been proposed recently. TAOs aim at spreading equitable value distribution and democratized decision-making, distinguishing them from their DAOs counterparts. This study focuses on the treasury within TAOs, which acts as a central fund pool and a crucial element in the decentralized economy (DeEco) system. First, against a backdrop of potential black swan events and other long-tail unforeseen challenges, a reference model for the intelligent treasury management of TAOs is proposed. Then, an evaluation system, namely VALID, is presented with metrics including verifiability, anti-volatility, legitimacy, inclusiveness, and decentralization. Furthermore, a novel parallel treasury management mechanism is proposed to demonstrate a virtual-real interactive closed-loop management and control paradigm of the treasury, thereby fostering the formulation and development of DeEco. This research provides a comprehensive perspective on intelligent treasury management of TAOs and their role in sustainable advancement of DeEco.
Kausthav Pratim Kalita, Debojit Boro, Dhruba K. Bhattacharyya
Abstract The rise of technology has resulted in the evolution of data generation at a rapid speed. With the high increase in the volume of data, it has become necessary to store it using reliable and scalable data management systems. Blockchain offers a storage structure that ensures the security and reliability of the stored data. Smart contracts further enhance the technology by enforcing more stringent record management activities. In recent times, there has been widespread utilization of IPFS in conjunction with blockchain technology. This utilization facilitates the establishment of decentralized and distributed data storage, as well as the connection of blockchain transactions to external data, thereby enhancing scalability and reducing storage expenses within blockchain applications. This paper introduces an effective collaborative ecosystem called SSE_CIB, where images undergo multiple operations including quantization before getting uploaded to IPFS. The image‐related details are stored in the blockchain to keep track of record entries. In our approach, a watermarking process has also been included to ensure the protection of copyright. Further, the images undergo block‐wise rotation based on a secret key and bit‐wise operation with a key image for enhanced security and protection. The work is implemented and tested using real‐life images in an Ethereum environment incorporated with a smart contract that enables proper execution of transactions.
Open access
Advanced Steganography and Watermarking Techniques
Muhammad Ahmad Ashfaq, Nimra Haq, Usman Arshad, Muhammad Shoaib Farooq · 5 authors
ATMs generate vast amounts of data daily, which needs to be analyzed and stored. Dealing with this data, also termed big data, is a complex task, and here comes the role of ETL pipelines. ETL pipelines need extensive resources for operations, and their performance optimization is necessary as data must be dealt with in near or even real-time. If the pipeline deals with financial data such as ATM transactions, steps should be taken to ensure the data's security, privacy, confidentiality, and integrity. This can be achieved using Blockchain technology. It is a distributed ledger technology having an immutable nature. It has significant advantages in terms of providing security, but it has disadvantages as well, such as low throughput and transactional latency. If blockchain is used in an ETL pipeline, it will affect the overall performance. So, to prevent the decline in performance, steps should be taken to optimize it. In this paper, we are using parallelization and partitioning as techniques to optimize performance. The primary goal here is to achieve maximum security while maintaining performance.
In this paper, we deal with the estimation of two widely used risk measures such as Value-at-Risk (VaR) and Expected Shortfall (ES) in a cryptocurrency context. To face the presence of regime switching in the cryptocurrency volatilities and the dynamic interconnection between them, we propose a Monte Carlo-based approach using heteroskedastic factor analysis and hidden Markov models (HMM) combined with a structured variational Expectation-Maximization (EM) learning approach. This composite approach allows the construction of a diversified portfolio and determines an optimal allocation strategy making it possible to minimize the conditional risk of the portfolio and maximize the return. The out-of-sample prediction experiments show that the composite factorial HMM approach performs better, in terms of prediction accuracy, than some other baseline methods presented in the literature. Moreover, our results show that the proposed methodology provides the best performing crypto-asset allocation strategies and it is also clearly superior to the existing methods in VaR and ES predictions.
This paper explores the development of ERC-404 tokens within the Ethereum blockchain ecosystem and investigates strategies for enhancing digital asset growth. The paper finds effective methods for developing ERC-404 tokens and examines their effects on digital asset management through a thorough literature review and data analysis. For blockchain developers, investors, and enthusiasts looking to use ERC-404 tokens for long-term growth in the digital asset market, the findings offer insightful information. In the digital age, blockchain technology and cryptocurrencies have completely changed how we see and exchange value. Ethereum has become a prominent platform for token production and decentralised apps (DApps) among the many blockchain-based assets. Token interfaces and protocols within the Ethereum ecosystem are defined by ERC standards, which were created by Ethereum Improvement Proposals (EIPs). For example, ERC-20 tokens have become widely used due to their interoperability and fungibility. However, as the blockchain industry's requirements change, there is a growing need for specialised token standards suited to particular use cases. This paper focuses on ERC-404 tokens, a proposed standard designed to address the limitations of existing token standards and facilitate innovative digital asset management solutions.
This paper analyses the legal framework of national virtual currencies and so-called Central Bank Digital Currencies (CBDCs) from a comparative law perspective. The authors define the meaning of the terms “means of payment” and “legal tender” and determine the legal consequences of classifying certain means of payment as legal tender. Building on this, the authors present new developments in the field of sovereign virtual currencies and shed light on their evolution through a comparative legal analysis of various national virtual currencies. In this context, the authors present developments in various African countries, Venezuela’s initiative to introduce the first state-backed crypto token, the first CBDC pilot projects in Uruguay and China, and considerations to introduce a CBDC in the EU. Based on the analyzed systems, problems regarding privacy, user protection and effective regulation of transactions are highlighted in order to present the legal challenges for the establishment of a fully functional (supra-)national euro CBDC.
Distributed Outsourced Storage systems, exemplified by the InterPlanetary File System (IPFS), offer compelling alternatives to traditional centralized cloud storage by emphasizing resilience and openness. Advancing this paradigm, Decentralized Storage (DS) markets leverage distributed ledgers to facilitate the monetization of outsourced storage. However, these markets often prioritize security over cost-efficiency, leading to high costs in existing DS markets. In our work, we introduce a middleware service, DWare, utilizing trusted hardware to balance security and cost efficiency. DWare offers two key advantages: 1) It enhances storage auditing efficiency by delegating computational tasks and standardizing the batched audit process. This approach offers a more feasible solution for validating outsourced storage with recurring pay-offs. 2) It implements secure and verifiable data deduplication, thereby increasing storage efficiency and reducing operational costs. This step, commonplace in cloud storage services, remains largely unexplored in current DS designs. While DWare could empirically reduce costs to levels near raw storage fees, it entails certain security concessions due to middleware involvement. To address this, we propose a hybrid trust security model, granting data owners the flexibility to adjust the security-cost balance as needed.
Mahsa Bastankhah, Viraj Nadkarni, Xuechao Wang, Chi Jin · 6 authors
Decentralized finance (DeFi) borrowing and lending platforms are crucial to the decentralized economy, involving two main participants: lenders who provide assets for interest and borrowers who offer collateral exceeding their debt and pay interest. Collateral volatility necessitates over-collateralization to protect lenders and ensure competitive returns. Traditional DeFi platforms use a fixed interest rate curve based on the utilization rate (the fraction of available assets borrowed) and determine over-collateralization offline through simulations to manage risk. This method doesn't adapt well to dynamic market changes, such as price fluctuations and evolving user needs, often resulting in losses for lenders or borrowers. In this paper, we introduce an adaptive, data-driven protocol for DeFi borrowing and lending. Our approach includes a high-frequency controller that dynamically adjusts interest rates to maintain market stability and competitiveness with external markets. Unlike traditional protocols, which rely on user reactions and often adjust slowly, our controller uses a learning-based algorithm to quickly find optimal interest rates, reducing the opportunity cost for users during periods of misalignment with external rates. Additionally, we use a low-frequency planner that analyzes user behavior to set an optimal over-collateralization ratio, balancing risk reduction with profit maximization over the long term. This dual approach is essential for adaptive markets: the short-term component maintains market stability, preventing exploitation, while the long-term planner optimizes market parameters to enhance profitability and reduce risks. We provide theoretical guarantees on the convergence rates and adversarial robustness of the short-term component and the long-term effectiveness of our protocol. Empirical validation confirms our protocol's theoretical benefits.
Abstract This paper provides an overview of the distributed ledger technology (DLT) options available to central banks for issuing central bank digital currency (CBDC). We discuss the main requirements that a DLT solution must fulfill and analyze the various structures for implementation offered by DLT — public, permissioned and private — and the implications that each has for the central bank and the existing financial system. While a CBDC built on an open, permissionless system would provide the full functionality offered by DLT, it is also far more disruptive to the existing financial system and consequently requires more new infrastructure on the part of the central bank.
The InterPlanetary File System (IPFS) has emerged in 2015 as a promising peerto-peer (P2P) distributed file-sharing system poised to become the backbone of Web3.However, its BitSwap protocol, responsible for block exchange, encounters redundancy issues when multiple peers respond with duplicate blocks.To address this limitation, we propose CodedBitSwap, an innovative network coding-based data exchange protocol that integrates Random Linear Network Coding (RLNC) into BitSwap.Considering that RLNC operations incur additional computational overhead, the RLNC-based protocol is designed with careful attention to its computational complexity that is investigated through trial experiments guiding the selection of coding parameters and structures.To assess the feasibility and performance of CodedBitSwap, an experimental evaluation that compares it with BitSwap was conducted in different scenarios xv using a controlled testbed environment consisting of 11 nodes exchanging three files of different sizes.During file exchange, the amount of data transmitted, download time, and encoding and decoding times were measured for each node.The evaluation results demonstrate that CodedBitSwap effectively eliminates redundancy at a relatively low cost of increased download time.The introduced RLNC computational complexity was optimized by the generation-based design strategy that minimizes it, ensuring that the cost of the reduced redundancy remains relatively low.The undertaken design methodology of CodedBitSwap offers a practical approach for future systems, which balances the overhead of RLNC coding with the benefits it brings.This work contributes to the advancement of network coding in P2P networks and demonstrates its potential to improve the efficiency of IPFS, opening up avenues for future research.
Non-fungible tokens (NFTs) are digital identifiers containing metadata, such as token number, title, content, and image URL, and are linked to digital assets, which are characterized by the fact that, unlike conventional virtual assets, they have their own unique value and cannot be replaced. NFTs cannot be deleted or forged; therefore, they can be used to authenticate the ownership of digital assets. The metadata of the NFTs are uploaded to the interplanetary file system (IPFS), which is a distributed file system, and converted into unique content identifiers (CIDs) that are stored on the blockchain. Digital content (DC) is divided into multiple pieces; it also has its own unique value and is distributed and stored using the IPFS. This study built an NFT-based IPFS testbed and experimented with the process of generating unique values for DC divided into three groups and sharing them. The results confirmed that each DC had a unique hash value and no duplicates existed.
Iveta Grigorova, Aleksandar Karamfilov, Radostin Merakov, A. S. Efremov
In a rapidly evolving and often volatile crypto market, the ability to use historical data for simulations provides a more realistic assessment of how decentralized finance (DeFi) protocols might perform. This insight is crucial for participants, developers, and investors seeking to make informed decisions. This paper presents a comprehensive study evaluating the dynamic performance of a newly developed DeFi protocol—NOLUS. The main objective of this paper is to present and analyze the built realistic model of the platform. This model could be successfully used to analyze the stability of the platform under different environmental influences by performing various simulations and conducting experiments with different parameters that could not be realized with the real platform. In the article, the key components of the platform are presented in detail and the main dependencies between them are clarified, in addition to the ways of forming multiple variables, and the complex relations between them in the real protocol are explained. The main finding from the experimental part of the study is that the performance of the protocol representation accounts for the expected system behavior. Hence the system simulation could be successfully used to reveal essential protocol behaviors resulting from potential shifts in the crypto market environment and to optimize the protocol’s hyper parameters.
We present the Layered Merkle Patricia Trie (LMPT), a performant storage data structure for processing transactions in high-throughput systems when compared to traditional Merkle Patricia Tries used in Ethereum clients. LMPTs keep smaller intermediary tries in memory to alleviate read and write amplification from high-latency disk storage. As an additional feat, they also allow for the I/O and transaction verifier threads to be scheduled in parallel and independently. LMPTs can ultimately reduce significant I/O traffic that happens on the critical path of transaction processing. Empirical results show that LMPTs can process up to$\times6$more transactions per second on real-life ERC20 smart contract workloads when compared to existing Ethereum clients.