In decentralized finance (DeFi), stablecoins like DAI are designed to offer a stable value amidst the fluctuating nature of cryptocurrencies. We examine the class of crypto-backed stable derivatives, focusing on mechanisms for price stabilization and exemplified by the well-known stablecoin DAI from MakerDAO. For simplicity, we consider a single-collateral setting. We introduce a belief parameter to the simulation model of DAI in a previous work (DAISIM), reflecting market sentiments about the value and stability of DAI, and show that it better matches the expected behavior when this parameter is set within a particular range of values. Our methods include comparing simulated data with real-world data, focusing on monthly correlations between ETH and DAI prices and scatter plots illustrating the relationship of their price trends over time. We also propose a simple mathematical model of DAI price to explain its stability and dependency on ETH price. Finally, we analyze possible risk factors associated with these stable derivatives to provide valuable insights for stakeholders in the DeFi ecosystem.
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.
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.
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.
Abusaid Manap, Gulnara Abitova, Gulzhan Uskenbayeva, Aigul Shaikhanova
In the era of pervasive digital data, ensuring secure file storage has become a paramount concern. This paper explores the significance of hybrid cryptography in the development of information technology for secure file storage. Hybrid cryptography, combining symmetric and asymmetric encryption, offers robust protection against unauthorized access, tampering, and data loss. The article reviews recent cryptography literature, highlighting the importance of secure file storage in today's interconnected world and examining the benefits of hybrid cryptography. The analysis of articles on cryptography reveals emerging trends and challenges. Post-quantum cryptography addresses concerns about quantum threats, while blockchain-based cryptography enhances security in IoT data sharing. Homomorphic encryption enables computations on encrypted data, and privacy-preserving cryptographic protocols facilitate secure multi-party computation. Machine learning's intersection with cryptanalysis introduces efficiency but raises ethical considerations. The paper further discusses advancements and trends in cryptography techniques, including post-quantum cryptography, homomorphic encryption, zero-knowledge proofs, post-quantum key exchange, secure multi-party computation, and post-quantum signature schemes. These developments aim to ensure long-term security against quantum attacks, enable privacy-preserving computations, and enhance the confidentiality, integrity, and authentication of digital communication and data storage. In conclusion, the paper advocates for the adoption of hybrid cryptography in secure file storage systems. Its combination of symmetric and asymmetric encryption, along with its adaptability to evolving security landscapes, positions hybrid cryptography as a formidable approach to data protection. By embracing hybrid cryptography and staying informed about the latest advancements, organizations can navigate the digital age with confidence, ensuring the confidentiality, integrity, and availability of stored files.
Nothing prevents several Non Fungible Tokens (NFTs) to be associated to the same digital asset, for instance, an image. As a consequence, the NFTs ecosystem is flooded with NFT replicas associated to the same assets of famous NFTs. The purpose of this paper is to propose creating NFTs in such a way that NFT/asset combination can not be replicated. We call the NFTs created in this way, Authentic NFTs. NFT token ids are known in advance, before creating the NFTs. Our approach is to include the NFT token id in the digital asset, and have the asset being digitally signed by it’s creator (author/artist). Given that NFT IDs are unique, our main finding is that any Authentic NFT replica can not be authentic. Either the NFT replica id does not match the NFT ID in the asset (if the asset was not modified), or the NFT replica asset is not signed by the asset creator (if the asset was modified).
Open access
Advanced Steganography and Watermarking Techniques
Ethereum introduced Transaction Access Lists (TALs) in 2020 to optimize gas costs during transaction execution. In this work, we present a comprehensive analysis of TALs in Ethereum, focusing on adoption, quality, and gas savings. Analyzing a full month of mainnet data with 31,954,474 transactions, we found that only 1.46% of transactions included a TAL, even though 42.6% of transactions would have benefited from it. On average, access lists can save around 0.29% of gas costs, equivalent to approximately 3,450 ETH (roughly US$ 5 Mio) per year. However, 19.6% of TALs included by transactions contained imperfections, causing almost 11.8% of transactions to pay more gas with TAL than without. We find that these inaccuracies are caused by the unknown state at the time of the TAL computation as well as imperfect TAL computations provided by all major Ethereum clients. We thus compare the gas savings when calculating the TAL at the beginning of the block vs. calculating it on the correct state, to find that the unknown state is a major source of TAL inaccuracies. Finally, we implement an ideal TAL computation for the Erigon client to highlight the cost of these flawed implementations.
The Log-Structure Merged tree (LSM-tree) based key-value (KV) store has been widely adopted as the storage engine for blockchain systems, such as Ethereum, in which blockchain data are uniformly transformed into randomly distributed KV items for persistence. However, blockchain semantics are ignored during this process, making the blockchain storage suffer from heavy read/write amplification problems. Moreover, as the Ethereum network scales up, tremendous data further exacerbates its storage burden. Until now, most studies have focused on sharding, data archiving, decentralized distributed storage, etc., to mitigate the burden of the storage layer. However, the incompatibility between Ethereum semantics and the characteristics of the storage engine is ignored. In this paper, we present ChainKV, a new semantics-aware storage paradigm to improve the storage management performance for the Ethereum system. Firstly, based on Ethereum blockchain semantics, ChainKV separately stores different types of data in multiple storage zones in the KV store to mitigate the read/write amplification problem. Secondly, following the mechanism of the verification process in the authenticated data structure (ADS), a new ADS data transformer is proposed to exploit the data locality when persisting ADS. Moreover, a new space gaming caching policy is adopted to coordinate the cache space management for two independent storage zones. Finally, we propose an optional lightweight node crash recovery mechanism to eliminate functional redundancy between the Ethereum protocol and the storage engine. The experimental results indicate that ChainKV outperforms the prior Ethereum systems by up to 1.99× and 4.20× for synchronization and query operations, respectively
Saidu Sokoto, Michał Król, Vladimir Stanković, Étienne Rivière
Distributed Hash Tables (DHTs) serve as the backbone of numerous modern decentralized systems like the InterPlanetary File System (IPFS) and Ethereum. As these systems evolve and expand, there is a growing need to enhance and optimize their underlying network support. In response to these challenges, we embark on the development of a new class of DHTs, marked by efficiency, security, and suitability for real-world deployments. We achieve this by making changes in the routing procedures, incorporating latency-aware routing, and harnessing recent hardware advancements.
Digital currencies have become an increasingly popular topic of discussion in recent years. Digital currencies are virtual forms of currency that operate outside the traditional banking system. They are based on cryptographic technologies and are often decentralized, meaning they are not controlled by a central authority. The most well-known digital currency is Bitcoin, but there are many other types of digital currencies in existence. Digital currencies can be used to purchase goods and services online or transferred between users directly without intermediaries like banks. They have gained popularity due to their potential for increased security, transparency, and efficiency in financial transactions. In today's digital currency, a variety of digital currencies emerge in an endless stream, and crypto technology is also constantly developing to improve the security of digital currency payments. In section 2, this paper briefly introduces several common digital currencies and encryption algorithms, and in section 3, this paper introduces these typical digital currencies in detail through the analysis of representative literature. Bitcoin is mainly encrypted based on blockchain technology, and its encryption principle is mainly divided into three parts: public key encryption, hash function, and proof of work. Ethereum is a distributed blockchain platform with encryption principles similar to Bitcoin, including public key encryption and hashing algorithms. Ripple is a distributed cryptocurrency. Its encryption principle mainly adopts the public-private key encryption system. In terms of encryption technology, blockchain technology, the Hash algorithm and symmetric and asymmetric encryption are also popular encryption algorithms in digital currencies.
Logging is a critical function to enable auditing and enhance security of distributed applications. This paper describes the design of Mnemosyne, a distributed logger running over Named Data Networking(NDN), to meet this need for NDN-based distributed applications. Mnemosyne assures the immutability of logged events by interlocking all event records in a DAG-based ledger. Mnemosyne provides a high logging throughput and system resiliency against network component failures. We implemented Mnemosyne and evaluated its design through an emulated deployment setting.
Leonhard Balduf, Maciej Korczyński, Onur Ascigil, Navin V. Keizer · 7 authors
Interplanetary Filesystem (IPFS) is one of the largest peer-to-peer filesystems in operation. The network is the default storage layer for Web3 and is being presented as a solution to the centralization of the web. In this paper, we present a large-scale, multi-modal measurement study of the IPFS network. We analyze the topology, the traffic, the content providers and the entry points from the classical Internet. Our measurements show significant centralization in the IPFS network and a high share of nodes hosted in the cloud. We also shed light on the main stakeholders in the ecosystem. We discuss key challenges that might disrupt continuing efforts to decentralize the Web and highlight multiple properties that are creating pressures toward centralization.