Digital marketing has transformed referral marketing, revealing limitations in traditional centralized systems such as trust, transparency, and efficiency, however, the potential advantages of decentralized systems remain underexplored. This paper investigates the feasibility of a high-volume, decentralized referral system. The approach assesses smart contract prototypes for cost-effectiveness and performance in high-user engagement scenarios in different EVM-compatible blockchains and referral strategies, such as multilevel referrals. Findings confirm the technical viability as a blueprint for designing and implementing similar systems, highlighting challenges in real-world deployments, such as Sybil attacks, and the interplay between technical and economical design factors.
In this paper, we consider DAG-based Distributed Ledger Technologies (DLTs), i.e., DLTs where each block can reference several previous blocks hence forming a Directed Acyclic Graph of Blocks (BDAG). Each block has a weight (usually a constant normalized to one) and our goal is to compute the heaviest sub-BDAG that does not contain conflicting blocks. First, we prove that computing such a sub-BDAG is NP-complete. Then, we show that the difficulty comes from con-current conflicts and we present an optimal algorithm that is polynomial if the number of concurrent conflicts is bounded. Finally, we evaluate the performance of our algorithm on random BDAGs against an existing algorithm called GHOSTDAG and show that, in addition to being optimal, our algorithm is also more efficient in practice.
This paper addresses the problem of blockchain scalability, problem that might be detrimental to their widespread adoption. Blockchain data can be categorized into both an application part and a consensus part, the latter one growing linearly over time. The authors in [1] provably solves this problem in the context of work-based blockchains. Their solution achieves an exponential reduction both for storage and communication assuming a static mining difficulty, that is assuming that the blockchain is beeing built by a fixed number of miners. This paper improves upon this work by handling variable mining difficulty. Experimental results show that our solution still guarantees exponential reduction of both storage and communication.
This paper addresses the challenge of interoperability between blockchain networks in healthcare. It presents a new conceptual model that uses non-fungible tokens (NFTs) to promote seamless communication between different blockchain systems. These tokens play a key role in securing data exchange and protecting medical information by serving as unique identifiers. Expected outcomes of this approach include improved interoperability, streamlined workflows, and improved patient outcomes.
The Move language provides superior security and verifiability compared to existing smart contract languages such as Solidity. As the language becomes more popular, gas optimization will become an important field of research. This paper presents the first work on gas optimization in the Move language. We chose Aptos as the underlying platform for our analysis since it is the leading Move-enabled blockchain platform, and it was the first to develop a gas meter. In this paper, we describe Aptos' gas meter in detail. Then, we analyze the vast research on gas optimization in Solidity, and explore how it can be implemented in the Move language. Finally, this paper proposes 11 gas optimization patterns and principles for the Move language, presents 5 patterns that decrease the time complexity of the smart contract but have no effect on gas consumption, and implements a sample smart contract for each proposed gas optimization pattern. Our results show that the proposed patterns reduce gas consumption in a typical smart contract by 7 – 56%.
In blockchains, the number of transactions in each block is limited. In order to determine which transactions are included, a fee-based model is regularly used. At the same time, zk-rollups, which are often used as a layer 2 scalability solution for blockchains, are based on the same underlying fee model. In this paper we propose studying the inclusion of transaction flow control algorithms in zk-proofs to investigate alternative transaction fee models in zk-rollups or validiums by enabling proven flow control. We study the provability and the cost of control algorithms that manage the flow of transactions, preventing excessive volume and spamming. The evaluation of our proposition, based on our minimal zk-rollup implementation, demonstrates the effectiveness of these algorithms and their relative proof generation complexity. This can lead to new applications that need anti-spam protection or new fee models in a secure environment.
Smart contract access control mechanisms can introduce centralization into supposedly decentralized ecosystems. In our view, such centralization is an overlooked risk of smart contracts that underlies well-known smart contract security incidents. Critically, mitigating the known vulnerability of missing permission verification by implementing authorization patterns can in turn introduce centralization. To delineate the issue, we define centralization risk and describe smart contract source code patterns for Ethereum and Algorand that can introduce it to smart contracts. We explain under which circumstances the centralization can be exploited. Finally, we discuss implications of centralization risk for different smart contract stakeholders.
Uniswap is currently the most liquid Decentralized Exchange (DEX) on Ethereum. In May 2021, it upgraded to the third protocol version named Uniswap V3. The key feature update is “concentrated liquidity”, which supports liquidity provision within custom price ranges. However, this design introduces a new type of Miner Extractable Value (MEV) source called Just-in-Time (JIT) liquidity attack, where the adversary mints and burns a liquidity position right before and after a sizable swap. We begin by formally defining the JIT liquidity attack and subsequently conduct empirical measurements on Ethereum. Over a span of 20 months, we identify 36,671 such attacks, which have collectively generated profits of 7,498 ETH. Our analysis suggests that the JIT liquidity attack essentially represents a whales' game, predominantly controlled by a select few bots. The most active bot, identified as 0xa57…6CF, has managed to amass 92% of the total profit. Furthermore, we find that this attack strategy poses significant entry barriers, as it necessitates adversaries to provide liquidity that is, on average, 269 times greater than the swap volume. In addition, our findings reveal that the JIT liquidity attack exhibits relatively poor profitability, with an average Return On Investment (ROI) of merely 0.007%. We also find this type of attack to be detrimental to existing Liquidity Providers (LPs) within the pool, as their shares of liquidity undergo an average dilution of 85%. On the contrary, this attack proves advantageous for liquidity takers, who secure execution prices that are, on average, 0.139% better than before. We further dissect the behaviors of the top MEV bots and evaluate their strategies through local simulation. Our observations reveal that the most active bot, 0xa57…6CF, conducted 27% of non-optimal attacks, thereby failing to capture at least 7,766 ETH (equivalent to 16.1M USD) of the potential attack profit.
In recent years, blockchain technology has spread widely in the agri-food sector. In particular, several blockchain-based tracking systems have been proposed. Most of these projects use mature technologies, such as Ethereum and Hyper-ledger. However, other blockchains were proposed recently (some particularly suited to IoT, commonly used in agri-food tracking systems). In the literature, several methodologies are proposed to guide the choice of the type of blockchain. These methodologies are generic, and a gap remains between the criteria used to guide the selection of the type of blockchain and how concrete use cases influence them. Building upon existing methodologies, this paper presents a specific approach for agri-food tracking. Once the parameters of the use case that impact the blockchain's performance have been identified, the methodology allows the association of these parameters with the criteria for identifying the types of blockchain to use (e.g., public permissionless) and the most suitable consensus algorithm. The output tuple \ [types], [algorithms], [functions]), therefore, allows the choice of the blockchain that best suits the usage scenario.
Early open blockchain designs face low throughput, high latency, and prohibitive costs for setting up a full node. New designs improve this with innovative mechanisms for handling transactions and the blockchain state, often assuming locality properties in the workload of transactions. Temporal locality allows efficient space management such as light nodes or snapshot-based bootstrap. Disjoint access parallelism, which depends on spatial locality, enables parallel processing of non-conflicting transactions. We analyze locality properties and their interplay in the largest transactional workload available to date, that of Ethereum. Our results show that, although transactions generally display good locality, a minority of accounts are responsible for caching- or parallelism-unfriendliness, calling for specific identification and handling in future blockchain designs.
In Blockchain technology, distributed computing is based on trust assumption among independent nodes. Researchers are in never ending race to address the Blockchain scalability issues. In this research paper, Prioritised Sharding is introduced which is an innovative strategy based on prioritising nodes according to their performance using real-time analytics and advanced algorithms to enhance the scalability of Blockchain systems. Experimental results demonstrate notable improvements in query response times, data availability, and overall system throughput. Furthermore, our model reduces the potential bottlenecks typically associated with traditional sharding techniques. This work contributes significantly to the discourse on scalable data management strategies and offers promising applications for large-scale, data-intensive enterprises.
Blockchains require deterministic execution in order to reach consensus. This is often guaranteed in languages designed to write smart contracts, such as Solidity. Application-specific blockchains or “appchains” allow the blockchain application logic to be written using general-purpose programming languages, giving developers more flexibility but also additional responsibilities. In particular, developers must ensure that their blockchain application logic does not contain any sources of non-determinism. Any source of non-determinism may be a potential source of vulnerabilities. This paper focuses on the use of Static Application Security Testing (SAST) tools to detect such sources of non-determinism at development time. We focus on Cosmos, a prominent open-source project that lets developers build interconnected networks of application-specific blockchains. Cosmos provides a Software Development Kit (SDK) that allows these chains to be implemented in the Go programming language. We create a corpus of 11 representative Cosmos-based appchains to analyze for sources of non-determinism in Go. As part of our study, we identified cosmos-sdk-codeql, a set of CodeQL code analysis rules for Cosmos applications. We find that these rules generate many false positives and propose a refactored set of rules that more precisely detects sources of non-determinism only in code that runs as part of the blockchain logic. We demonstrate a significant increase in the precision of the rules, making the SAST tool more effective and hence potentially contributing to enhanced security for Cosmos-based blockchains.
In blockchain space, access control is a crucial aspect of smart contract development, as it guarantees that only authorized users can execute specific functions within a contract. The growing interest in employing smart contracts for access control mechanisms stems from their ability to provide reliable, secure and efficient enforcement of access control policies. However, Solidity, the most popular smart contract language, was not designed explicitly for writing access control policies, unlike specialized languages such as Alfa or XACML. The differences between these languages leads to a difficulty for those who wish to use smart contracts as access control mechanisms but lack the knowledge of Solidity or the ability to evaluate their code's security. To bridge this gap, we introduce ASAC, an Alfa to Solidity transpiler that translates Alfa policies into secure Solidity contracts. Our transpiler leverages the ANTLR (ANother Tool for Language Recognition) parser generator and translate complex Alfa policies into smart contracts. We showcase the effectiveness of our transpiler through a set of case studies and offer an evaluation of its performance.
In recent years, cryptocurrencies have gained a lot of popularity in the financial markets and now, in addition to investing on them, it is possible to use them as a common currency to meet daily needs. Given the complex nature of financial markets and their reliance on different parameters to determine stocks' and assets' prices, the ability to predict prices is important for investment decisions, especially with respect to cryptocurrencies. To this end, Deep Learning (DL)-based algorithms can be viable solutions, owing to their use as time series forecasting tools. In this paper, we investigate the applicability of DL algorithms to forecast the prices of three cryptocurrencies, namely Bitcoin, Ethereum, and Ripple. We evaluate the performance of the proposed approach, in terms of short-term and long-term prediction accuracy (considering proper error metrics).
While blockchain is a secure and tamper-proof registry, it is not well-suited for storing large amounts of data due to its limited storage capacity and high cost. Additionally, storing data on a blockchain can lead to scalability issues and slow down the network. Therefore, it is generally not recommended to store large amounts of data on a blockchain. This paper proposes a solution to transmit data to smart contracts without compromising security with a single point of failure, using a bounty hunting mechanism to ensure fair concurrency between oracles retrieving data on an IPFS database. The proposed solution has been implemented as a prototype and its feasibility has been demonstrated through experiments.
This paper investigates the issue of fairness in Distributed Ledger Technology (DLT), specifically focusing on the shortcomings observed in current blockchain systems due to Miner Extractable Value (MEV) phenomena and systemic centralization. We explore the potential of Directed Acyclic Graphs (DAGs) as a solution to address or mitigate these fairness concerns. Our objective is to gain a comprehensive understanding of fairness in DAG-based DLTs by examining its different aspects and measurement metrics. We aim to establish a shared knowledge base that facilitates accurate fairness assessment and allows for an evaluation of whether DAG-based DLTs offer a more equitable design. We describe the various dimensions of fairness and conduct a comparative analysis to examine how they relate to different components of DLTs. This analysis serves as a catalyst for further research, encouraging the development of cryptographic systems that promote fairness.
Blockchains are finding evermore applications. One underused application of blockchains is local currencies. Local currencies are currencies that circulate in a restricted area in purpose of growing the local economy by forcing local spending. We introduce the concept of geographical demurrage: money loses of its value the farther away it is spent. We construct four generic local cryptocurrencies: a simple one mimicking local paper money; a second that restricts spending to the dedicated geographical area; a third that utilizes geographical demurrage for maintaining the system, and a fourth that lifts the geographical restrictions and maintains geographical demurrage, thus creating a universal local cryptocurrency: a currency that loses value correspondingly to the distance between its point of reception and point of spending. So without the need to restrict spending to a given geographical zone, the currency will always encourage local spending, no matter where it is spent; yielding a universal local cryptocurrency we name LCoin.
Smart Contract (SC) Programming Languages (PL) are inspired by Non-SC PLs. Many, like Solidity, use an object-oriented approach with interfaces and inheritance-based sub-typing. However, the main focus of these concepts is on abstraction and extend-ability, whereas for SC Systems, robust, secure and composable SCs are of higher importance. Further, despite supporting inheritance, Solidity and other SC PLs fail to leverage the full benefits of the object-oriented paradigm when multiple SCs are involved. This work presents an approach to SC composability that enables highly composable and secure SCs by encapsulating logic in small traits that serve as interfaces.
The Open Radio Access Network (O-RAN) introduces openness and intelligence into the existing, tightly-coupled RAN ecosystem. Openness promotes collaboration among various vendors to provide diverse components (hardware, software, or both) for the RAN ecosystem, while intelligence handles complex network activities using Artificial Intelligence (AI). Although O-RAN design addresses many issues in traditional RANs, such as vendor lock-in, lack of flexibility, and limited innovation, it raises several management and security concerns related to collaboration, access management, privacy, trust, and availability. Distributed Ledger Technologies (DLTs) offer a viable method of establishing trust among entities, managing resources efficiently, and automating complex network tasks. Several DLT properties, such as distributed architecture, high automation through smart contracts, immutability, and transparency, could position DLT-based ideas as game changers in a multi-vendor O-RAN ecosystem. Furthermore, this technology has the potential to introduce new business models and establish secure and trusted micro-payments among vendors and network participants. In this paper, we first present a taxonomy for discussing existing O-RAN challenges. Based on the taxonomy, we then examine the possibility of incorporating DLT-based solutions in O-RAN architecture to address these challenges.
The transparent, decentralized, and immutable properties of public blockchains make them appealing for applications that could benefit from these properties, including e-auctions. However, the usage of blockchains for such applications is hindered by concerns related to privacy and performance. We introduce a hybrid solution for e-auctions, leveraging the advantages of both centralized processing and the immutable registration offered by a public blockchain. In this approach, bids are processed by the auctioneer, while the masked bids are recorded on the blockchain. Consequently, the identity of the winner and their bid value is publicly accessible, while the remaining bid values remain confidential, known only to the bidder and the auctioneer and verifiable against the public results of the auction. These bids remain sealed unless the bidder chooses to disclose them during a dispute event. In this paper, we explain the proposed solution and present empirical analysis of its performance drawing on the outcomes of our preliminary experiments. We elaborate achieving promised privacy while showing 50% improvement over blockchain-based verifiable sealed-bid auction involving fewer than 15 bidders.
