This paper presents EDSC, a novel smart contract platform design based on the event-driven execution model as opposed to the traditionally employed transaction-driven execution model. We reason that such a design is a better fit for many emerging smart contract applications and is better positioned to address the scalability and performance challenges plaguing the smart contract ecosystem. We propose EDSC's design under the Ethereum framework, and the design can be easily adapted for other existing smart contract platforms. We have conducted implementation using Ethereum client and experiments where performance modeling results show on average 2.2 to 4.6 times reduced total latency of event triggered smart contracts, which demonstrates its effectiveness for supporting contracts that demand timely execution based on events. In addition, we discuss example use cases to demonstrate the design's utility and comment on its potential security dynamics.
Hendrik Amler, Lisa Eckey, Sebastian Faust, Marcel Kaiser · 6 authors
The decentralized and trustless nature of cryptocurrencies and blockchain technology leads to a shift in the digital world. The possibility to execute small programs, called smart contracts, on cryptocurrencies like Ethereum opened doors to countless new applications. One particular exciting use case is decentralized finance (DeFi), which aims to revolutionize traditional financial services by founding them on a decentralized infrastructure. We show the potential of DeFi by analyzing its advantages compared to traditional finance. Additionally, we survey the state-of-the-art of DeFi products and categorize existing services. Since DeFi is still in its infancy, there are countless hurdles for mass adoption. We discuss the most prominent challenges and point out possible solutions. Finally, we analyze the economics behind DeFi products. By carefully analyzing the state-of-the-art and discussing current challenges, we give a perspective on how the DeFi space might develop in the near future.
Permissionless blockchains such as Bitcoin have excelled at financial services. Yet, opportunistic traders extract monetary value from the mesh of decentralized finance (DeFi) smart contracts through so-called blockchain extractable value (BEV). The recent emergence of centralized BEV relayer portrays BEV as a positive additional revenue source. Because BEV was quantitatively shown to deteriorate the blockchain's consensus security, BEV relayers endanger the ledger security by incentivizing rational miners to fork the chain. For example, a rational miner with a 10% hashrate will fork Ethereum if a BEV opportunity exceeds 4x the block reward. However, related work is currently missing quantitative insights on past BEV extraction to assess the practical risks of BEV objectively. In this work, we allow to quantify the BEV danger by deriving the USD extracted from sandwich attacks, liquidations, and decentralized exchange arbitrage. We estimate that over 32 months, BEV yielded 540.54M USD in profit, divided among 11,289 addresses when capturing 49,691 cryptocurrencies and 60,830 on-chain markets. The highest BEV instance we find amounts to 4.1M USD, 616.6x the Ethereum block reward. Moreover, while the practitioner's community has discussed the existence of generalized trading bots, we are, to our knowledge, the first to provide a concrete algorithm. Our algorithm can replace unconfirmed transactions without the need to understand the victim transactions' underlying logic, which we estimate to have yielded a profit of 57,037.32 ETH (35.37M USD) over 32 months of past blockchain data. Finally, we formalize and analyze emerging BEV relay systems, where miners accept BEV transactions from a centralized relay server instead of the peer-to-peer (P2P) network. We find that such relay systems aggravate the consensus layer attacks and therefore further endanger blockchain security.
As the development of smart cities, energy management systems have been changing from centralized management systems to distributed energy management systems for better energy efficiency. In the distributed energy management systems, while producing the energy from distributed users, there can be two types of users such that 1) users who have surplus energy generations and 2) users who lack energy generations compared to their demands. In this paper, to alleviate such imbalance of energy generation between distributed users, a peer to peer (P2P) based energy trading platform is proposed. Specifically, blockchain is one of emerging solutions in which transactions can be made reliably to achieve P2P transactions without any centralized broker intervention. Correspondingly, we implement the P2P energy trading platform under Ethereum's smart contract for reliable trading. The energy generated from distributed users at the proposed platform can be traded by utilizing the characteristics of Decentralize Application. Specifically, we provide the details of implementations of the proposed platform, which includes both hardware platform and software platform. Further, we establish a web page and an mobile application for monitoring the transaction information such as transaction details and energy prices, which can enhance users' accessibility. Finally, the demonstration of process of energy trading via web interface is represented.
Florian Spychiger, Paolo Tasca, Claudio J. Tessone
This study covers the evolutionary development of blockchain technologies over the last 11 years (2009–2019) and sheds lights on potential areas of innovation in heretofore unexplored sub-components. For this purpose, we collected and analyzed detailed data on 107 different blockchain technologies and studied their component-wise technological evolution. The diversity of their designs was captured by deconstructing the blockchains using the Tasca-Tessone taxonomy to build what we call the “ tree of blockchain ” composed of blockchain main and sub-components. With the support of information theory and phylogenetics, we found that most design explorations have been conducted within the components in the areas of consensus mechanisms and cryptographic primitives. We also show that some sub-components like Consensus Immutability and Failure Tolerance, Access and Control layer , and Access Supply Management have predictive power over other sub-components. We finally found that few dominant design models—the genetic driving clusters of Bitcoin, Ethereum, and XRP—influenced the evolutionary paths of most of the succeeding blockchains.
Decentralized application (DAPP), replacing traditional business logic and data access layer with block chain, is a new form of Internet service. Testing DAPP requires large-scale distributed systems. Performing experiments in a real system is costly and difficult. This article carefully analyses the process of block generation and synchronization and explains the reasons for the low efficiency of block chain system simulation. We incorporate fuzzy rule based model for enhancing the logging system in blockchain. Rules based on fuzzy are utilized inside system of fuzzy logic to obtain outcome on basis of input variables. The data of Ethereum and Bitcoin proves that the block generation interval conforms to the exponential distribution, and the real PoW calculation can be replaced with random numbers. Both block verification and network propagation processes have latency, which can be simulated with asynchronous messaging. Based on the above analysis, this article proposes a high-performance simulation method based on event-driven model, which is suitable for describing the communication and synchronization behave our of block chain networks. The method can effectively describe the block generation, the synchronization process between nodes, and supports different equity proof forms. Using this method, the performance of the PoW systemis tested. Under the ecs.c6.xlargeinstance,the simulation running speed reaches 782 times of actual system. Further experiments show that this method can be efficiently used in larger-scale networks and is an effective tool for DAPP developing and testing.
Human behavior as they engaged in financial activities is intimately connected to the observed market dynamics. Despite many existing theories and studies on the fundamental motivations of the behavior of humans in financial systems, there is still limited empirical deduction of the behavioral compositions of the financial agents from a detailed market analysis. Blockchain technology has provided an avenue for the latter investigation with its voluminous data and its transparency of financial transactions. It has enabled us to perform empirical inference on the behavioral patterns of users in the market, which we explore in the bitcoin and ethereum cryptocurrency markets. In our study, we first determine various properties of the bitcoin and ethereum users by a temporal complex network analysis. After which, we develop methodology by combining k -means clustering and Support Vector Machines to derive behavioral types of users in the two cryptocurrency markets. Interestingly, we found four distinct strategies that are common in both markets: optimists, pessimists, positive traders and negative traders. The composition of user behavior is remarkably different between the bitcoin and ethereum market during periods of local price fluctuations and large systemic events. We observe that bitcoin (ethereum) users tend to take a short-term (long-term) view of the market during the local events. For the large systemic events, ethereum (bitcoin) users are found to consistently display a greater sense of pessimism (optimism) towards the future of the market.
Nisita Weerasinghe, Tharaka Hewa, Maheshi B. Dissanayake, Mika Ylianttila · 5 authors
Local 5G Operator (L5GO) concept is one of the most prominent versatile applications of the 5G in the near future. The popularity of L5GOs will trigger a greater number of roaming and offloading events between mobile operators. However, existing static and the operator-assisted roaming and offloading procedures are inefficient for L5GO ecosystem due to poor service quality, data privacy issues, data transferring delays, excessive costs for intermediary parties and existence of roaming fraud. To address these challenges, we propose a blockchain / Distributed Ledger Technology (DLT) based service platform for L5GOs to facilitate efficient roaming and offload services. As the key contribution, blockchain-based smart contract scheme is proposed to establish dynamic and automated agreements between operators. By using smart contracts, we introduce several novel features such as universal wallet for subscribers, service quality based L5GO rating system, user-initiated roaming process and the roaming fraud prevention system to improve the operational quality of a L5GO. A prototype of the proposed platform is emulated with the Ethereum blockchain platform and Rinkeby Testnet to evaluate the performance and justify the feasibility of the proposal. Upon an extensive evaluation on the prototype, it was observed that the proposed platform offered benefits such as cost effective, more secure and reliable experience.
Blockchain technology is characterized by decentralization, traceability and tamper resistance. A decentralized application (Dapp) refers to a blockchain-based application deployed on Ethereum platform, with the aim to facilitate decentralized smart contracts and to prosper the blockchain ecosystem. In this paper, an in-depth analysis for the current decentralized applications is performed to reveal the structure and development situation of blockchain ecosystem. With a better understanding of the blockchain ecosystem, insights can be obtained for the Dapp developers as well as for the potential blockchain adopters. Furthermore, guidelines and suggestions are provided to inspire the business applications based on blockchain.
In most websites, the online rating system provides the ratings of products and services to users. Lack of trust in data integrity and its manipulation has hindered fulfilling user satisfaction. Since existing online rating systems deal with a central server, all rating data is stored on the central server. Therefore, all rating data can be removed, modified, and manipulated by the system manager to change the ratings in favor of the service or product provider. In this paper, an online rating system using distributed ledger technologies has been presented as the proposed system to solve all the weaknesses of current systems. Distributed ledger technologies are completely decentralized and there is no centralization on them by any institution. Distributed ledger technologies have different variants. Among distributed ledger technologies, blockchain technology has been used in the proposed rating system because of its support for smart contracts. In the proposed online rating system, the Ethereum platform has been chosen from different blockchain platforms that have a public permission network. In this system, the raters cannot rate unless they submit a request to the system and be authorized to take part in the online product rating process. The important feature of the Ethereum platform is its support for smart contracts, which can be used to write the rating contract in the Solidity language. Also, using Proof of Authority consensus mechanisms, all rating transactions are approved by the surveyors. Since in the real Ethereum system, each rating transaction is sent to the network by the raters, some gas must be paid for each rating transaction. However, since this method is expensive, TestNet blockchain can be used in the rating system. Finally, the proposed rating system was used for rating the restaurants of a website and its features were tested.
Nami Ashizawa, Naoto Yanai, Jason Paul Cruz, Shingo Okamura
Ethereum smart contracts are computer programs that are deployed and executed on the Ethereum blockchain to enforce agreements among untrusting parties. Being the most prominent platform that supports smart contracts, Ethereum has been targeted by many attacks and plagued by security incidents. Consequently, many smart contract vulnerabilities have been discovered in the past decade. To detect and prevent such vulnerabilities, different security analysis tools, including static and dynamic analysis tools, have been created, but their performance decreases drastically when codes to be analyzed are constantly being rewritten. In this paper, we propose Eth2Vec, a machine-learning-based static analysis tool that detects smart contract vulnerabilities. Eth2Vec maintains its robustness against code rewrites; i.e., it can detect vulnerabilities even in rewritten codes. Other machine-learning-based static analysis tools require features, which analysts create manually, as inputs. In contrast, Eth2Vec uses a neural network for language processing to automatically learn the features of vulnerable contracts. In doing so, Eth2Vec can detect vulnerabilities in smart contracts by comparing the similarities between the codes of a target contract and those of the learned contracts. We performed experiments with existing open databases, such as Etherscan, and Eth2Vec was able to outperform a recent model based on support vector machine in terms of well-known metrics, i.e., precision, recall, and F1-score.
Bilinear pairing is a fundamental operation that is widely used in cryptographic algorithms (e.g., identity-based cryptographic algorithms) to secure IoT applications. Nonetheless, the time complexity of bilinear pairing is$O(n^{3})$, making it a very time-consuming operation, especially for resource-constrained IoT devices. Secure outsourcing of bilinear pairing has been studied in recent years to enable computationally weak devices to securely outsource the bilinear pairing to untrustworthy cloud servers. However, the state-of-art algorithms often require to precompute and store some values, which results in storage burden for devices. In the Internet of Things, devices are generally with very limited storage capacity. Thus, the existing algorithms do not fit the IoT well. In this article, we propose a secure outsourcing algorithm of bilinear pairings, which does not require precomputations. In the proposed algorithm, the outsourcer side’s efficiency is significantly improved compared with executing the original bilinear pairing operation. At the same time, the privacy of the input and output is ensured. Also, we apply the Ethereum blockchain in our outsourcing algorithm to enable fair payments, which ensures that the cloud server gets paid only when he correctly accomplished the outsourced work. The theoretical analysis and experimental results show that the proposed algorithm is efficient and secure.
Hanlin Zhang, Peng Gao, Jia Yu, Jie Lin · 5 authors
Linear Regression (LR) is a classical machine learning algorithm which has many applications in the cyber physical social systems (CPSS) to shape and simplify the way we live, work and communicate. This paper focuses on the data analysis for CPSS when the Linear Regression is applied. The training process of LR is time-consuming since it involves complex matrix operations, especially when it gets a large scale training dataset In the CPSS. Thus, how to enable devices to efficiently perform the training process of the Linear Regression is of significant importance. To address this issue, in this paper, we present a secure, verifiable and fair approach to outsource LR to an untrustworthy cloud-server. In the proposed scheme, computation inputs/outputs are obscured so that the privacy of sensitive information is protected against cloud-server. Meanwhile, computation result from cloud-server is verifiable. Also, fairness is guaranteed by the blockchain, which ensures that the cloud gets paid only if he correctly performed the outsourced workload. Based on the presented approach, we exploited the fair, secure outsourcing system on the Ethereum blockchain. We analysed our presented scheme on theoretical and experimental, all of which indicate that the presented scheme is valid, secure and efficient.
This study examines the predictability of three major cryptocurrencies-bitcoin, ethereum, and litecoin-and the profitability of trading strategies devised upon machine learning techniques (e.g., linear models, random forests, and support vector machines). The models are validated in a period characterized by unprecedented turmoil and tested in a period of bear markets, allowing the assessment of whether the predictions are good even when the market direction changes between the validation and test periods. The classification and regression methods use attributes from trading and network activity for the period from August 15, 2015 to March 03, 2019, with the test sample beginning on April 13, 2018. For the test period, five out of 18 individual models have success rates of less than 50%. The trading strategies are built on model assembling. The ensemble assuming that five models produce identical signals (Ensemble 5) achieves the best performance for ethereum and litecoin, with annualized Sharpe ratios of 80.17% and 91.35% and annualized returns (after proportional round-trip trading costs of 0.5%) of 9.62% and 5.73%, respectively. These positive results support the claim that machine learning provides robust techniques for exploring the predictability of cryptocurrencies and for devising profitable trading strategies in these markets, even under adverse market conditions.
Data trading is ubiquitous in today's Internet. User data is often sensitive in nature, for example, medical records and sensitive health related information. Present data trade often does not capture the owner's consent or allow tracking of the sale of her data. Even during a sale, fairness is not guaranteed and both the data owner and the data buyer remains at risk of being cheated. In this paper, we propose an end-to-end protocol to trade sensitive information addressing the key issues of consent, traceability and fairness. We use blockchain as the arbitrator and tamper-resistant log. We implement a prototype of our protocol on Ethereum and show that our proposed solution is practical.
Healthcare is one of the most important sector where security is a major concern in Internet of Things integrated healthcare. The future generation vehicles are enabled with features of autonomous driving and accurate decision making. We can use such features in emergency vehicle routing with the help of Blockchain technology for collecting trustworthy road network information. In this work, we design and develop an emergency vehicle routing solution where each vehicle connects to the Ethereum Blockchain integrated with Open Source Routing Machine (OSRM). Blockchain enables secure information sharing among vehicles and the OSRM provides shortest trustworthy routes. The proposed approach reduces transit delay of the emergency vehicles while providing emergency healthcare services. Furthermore, the efficacy of the proposed approach has been shown through experimentation by implementing a smart contract in Blockchain based trust-worthy vehicle route generation.
Off-chain is a common approach to deal with the scalability problem of blockchain networks. It enables users to execute multiple payments without committing each of them to the blockchain by relying on predefined payment channels. A pair of users can employ a payment even without a direct channel between them, via routing the payment through off-chain channels involving other intermediate users. Users together with the off-chain channels form a graph, known as the off-chain network topology. The off-chain topology and the payment characteristics affect network performance such as the average number of intermediate users a payment is routed through, the amount of fees, or channel capacities needed to successfully route payments. In this paper, we study two basic problems in off-chain network design. First, efficiently mapping users to an off-chain topology with a known structure. Second, constructing a topology of a bounded number of channels that can serve well users with associated payments. We design algorithms for both problems and evaluate them based on real data from Raiden, the off-chain extension for Ethereum.
The Internet of Things (IoT) is expected to improve the individuals’ quality of life. However, ensuring security and privacy in the IoT context is a non-trivial task due to the low capability of these connected devices. Generally, the IoT device management is based on a centralized entity that validates communication and connection rights. Therefore, this centralized entity can be considered as a single point of failure. Yet, in the case of distributed approaches, it is difficult to delegate the right validation to IoT devices themselves in untrustworthy IoT environments. Fortunately, the blockchain may provide decentralization of overcoming the trust problem while designing a privacy-preserving system. To this end, we propose a novel privacy-preserving IoT device management framework based on the blockchain technology. In the proposed system, the IoT devices are controlled by several smart contracts that validate the connection rights according to the privacy permission settings predefined by the data owners and the stored record array of detected misbehavior of each IoT device. In fact, smart contracts can immediately detect the devices that have vulnerabilities and have been hacked or pose a threat to the IoT network. Therefore, the data owner’s privacy is preserved by enforcing the control over the own devices. For validation purposes, we deploy the proposed solution on a private Ethereum blockchain and give the performance evaluation.
David Hyland-Wood, Peter Robinson, Roberto Saltini, Sandra Johnson · 5 authors
Integration of space-based communications infrastructure within 5G networks presents specific challenges for spacecraft, namely a necessary rationalization of currently patchy communications security and the assurance of identity when conducting high-level spacecraft tasking and control operations. This chapter presents approaches to addressing both issues via the deployment of an enterprise Ethereum blockchain modified with a consensus algorithm appropriate for access by spacecraft. We discuss the applicability of enterprise Ethereum blockchains to the problem of spacecraft communication security, analyze the properties of blockchain consensus algorithms suitable for use with spacecraft, and suggest information architectures to allow secure spacecraft integration into 5G networks.
Explainable Artificial Intelligence (XAI) generates explanations which are used by regulators to audit the responsibility in case of any catastrophic failure. These explanations are currently stored in centralized systems. However, due to lack of security and traceability in centralized systems, the respective owner may temper the explanations for his convenience in order to avoid any penalty. Nowadays, Blockchain has emerged as one of the promising technologies that might overcome the security limitations. Hence, in this paper, we propose a novel Blockchain based framework for proof-of-authenticity pertaining to XAI decisions. The framework stores the explanations in InterPlanetary File System (IPFS) due to storage limitations of Ethereum Blockchain. Further, a Smart Contract is designed and deployed in order to supervise the storage and retrieval of explanations from Ethereum Blockchain. Furthermore, to induce cryptographic security in the network, an explanation's hash is calculated and stored in Blockchain too. Lastly, we perform the cost and security analysis of our proposed system.