Ricardo Borges dos Santos, Nunzio Marco Torrisi, Erick Reyann Kasai Yamada, Rodrigo Palucci Pantoni
The use of smart contracts and blockchain tokens to implement a consumer trustworthy ingredient certification scheme for commingled foods, i.e., recipe based, food products is described. The proposed framework allows ingredients that carry any desired property (including social or environmental customer perceived value) to be certified by any certification authority, at the moment of harvest or extraction, using the IGR Ethereum token. The mechanism involves the transfer of tokens containing the internet url published at the authority’s web site from the farmer all along the supply chain to the final consumer at each transfer of custody of the ingredient using the Cricital Tracking Event/Key Data Elements (CTE/KDE) philosophy of the Institute of Food Technologists (IFT). This allows the end consumer to easily inspect and be assured of the origin of the ingredient by means of a mobile application. A successful code implementation of the framework was deployed, tested and is running as a beta version on the Ethereum live blockchain as the IGR token. The main contribution of the framework is the possibility to ensure the true origin of any instance or lot of ingredient within a recipe to the customer, without harming the food processor legitimate right to protect its recipes and suppliers.
Public blockchains such as Ethereum and Bitcoin provide transparency and accountability, and have strong non-repudiation properties, but fall far short of enterprise privacy requirements for business processes. Consequently consortiums are exploring private blockchains to keep their membership and transactions private. However, private blockchains do not provide adequate protection against potential collusion by consortium members to revert the state of the blockchain. To countenance this, the private blockchain state may be "pinned" to a tamper resistant public blockchain. Existing solutions offering pinning to the public blockchain would reveal the transaction rate of the private blockchain, and do not provide a mechanism to contest the validity of a pin. Moreover, they require that all transactions and members of the private blockchain be revealed. These challenges are hampering the wider adoption of private blockchain technology. We describe the primary author's `Anonymous State Pinning approach', which overcomes these limitations and present a security proof to demonstrate pins can be challenged without compromising these properties. We perform a gas cost analysis of the implementation to estimate the operating cost of this technology, which shows that pinning a private blockchain at the rate of one pin per hour would cost US$508 per year. A hierarchical pinning approach is proposed which would allow many private blockchains to pin to a management blockchain which would then pin to Ethereum MainNet. This approach saves money, but at the cost of increased finality times.
The blockchain architecture is often envisioned as a potential mechanism for the automation microtransactions between interconnected IoT applications, as transactions could be directly enforced through the technical governance structure it provides. However, this chapter draws attention to the limitations of the blockchain architecture in providing tools for conflict management, which is here considered to be a vital for both governance and the legitimacy of the system. Although blockchain’s potential for conflict prevention is often emphasised, experiences from public blockchain networks such as Ethereum demonstrate that prevention is not sufficient but instead dispute resolution mechanisms are needed for addressing unpredictable events. To this end, alternative conflict management strategies have been developed for blockchain-related disputes. We assess these emergent redress mechanisms from the perspective of conflict management with specific attention to fairness of outcomes and due process rules. By making a distinction between systemic disputes and low intensity disputes we demonstrate how conflict management, governance and technological infrastructure converge on blockchain networks. This convergence, in turn, influences how fairness expectations and due process safeguards are formulated, causing concern for the fairness of emergent conflict management. The design of blockchain-based IoT applications should take into consideration the need for conflict management and particular attention should be paid to the fairness of such mechanisms, as these contribute to the fulfillment of fairness expectations, the legitimacy and predictability of governance structures and, in the end, feasibility of mainstream use.
Blockchain technology has become extremely popular, during the last decade, mainly due to the successful application in the cryptocurrency domain. Following the explosion of Bitcoin and other cryptocurrencies, blockchain solutions are being deployed in almost every aspect of transactional operations as a means to safely exchange digital assets between non-trusted parties. At the heart of every blockchain deployment is the consensus protocol, which maintains the consistency of the blockchain upon satisfying incoming transactions. Although many consensus protocols have been recently introduced, the most prevalent is Proof-of- Work, which scales the blockchain globally by converting the consensus problem to a competition based on cryptographic hash functions; a process called “mining”. The Proof-of- Work consensus protocol employs memory-hard algorithms in order to counteract ASIC or FPGA mining that may compromise the decentralization and democratization of the blockchain. Unfortunately, this leads to increased power consumption and scalability challenges since numerous processing units such as GPUs, FPGAs, and ASICs, are required to satisfy the ever-increasing operational requirements of blockchain deployments. In this paper, we perform an in-depth performance analysis and characterization of the most common memory-hard PoW algorithms running on NVIDIA GPUs. Motivated by our experimental findings, we apply a series of optimizations on Ethash algorithm, the consensus protocol of the Ethereum blockchain. The implemented optimizations accelerate performance by 14% and improve energy efficiency by 10% when executing on three NVIDIA GPUs. As a result, the optimized Ethash algorithm outperformed its fastest commercial implementation.
Recently, the term blockchain has been on everyones lips due to the media hype which has emerged around the cryptocurrency Bitcoin. Soon the blockchain paradigm has become an inspiration for additional applications next to cryptocurrencies. One type of such applications are smart contracts, i.e. programs which are executed on a blockchain network and move digital assets according to arbitrary pre-specified rules. Utilizing the combination of cryptographically secure mechanisms of a blockchain and the possibility to execute programs on a blockchain network results in promising use cases for the public and the private sector. In order to run smart contracts, a platform such as Ethereum can be used. In contrast to a public smart contract platform, a private version allows to configure some blockchain-specific parameters when setting up the system. Examples of these configuration parameters are the time passing between two consecutive blocks, the size of blocks, the hardware of the nodes running the blockchain software or simply the size of the network. However, how these and other parameters of a private Ethereum smart contract platform affect the performance of the system is still poorly understood. Moreover, it is not clear to which extent these parameters scale and which parameters represent the bottleneck of such systems. In order to tackle this problem, this thesis introduces a novel concept for measuring the performance and scalability of private Ethereum smart contract platforms. This concept is practically implemented in a framework which allows to automatically deploy differently configured private Ethereum smart contract platforms on the cloud for the purpose of gathering performance-related data. Based on the gathered data, various charts were created which visualize the effects on performance when changing a specific parameter. The results of the data analysis conducted show that the effect of variations in one parameter is highly dependent on the configuration of other parameters as well, especially when running the system near its limits. Nevertheless, a structure which depicts the bottlenecks of current private Ethereum smart contract platforms has been identified. Further research may be conducted in order to support additional Ethereum clients and APIs.
Cryptocurrency is playing an increasingly important role in reshaping the financial system due to its growing popular appeal and mechant acceptance. While many people are making investments in Cryptocurrency, the dynamical features, uncertainty, the predictability of Cryptocurrency are still mostly unknown, which dramatically risk the investments. It is a matter to try to understand the factors that infiuence the value formation. In this study, we use advanced artificial intelligence frameworks of fully connected Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM) Recurrent Neural Network to analyse the price dynamics of Bitcoin, Etherum, and Ripple. We find that ANN tends to rely more on long-term history while LSTM tends to rely more on short-term dynamics, which indicate the efficiency of LSTM to utilise useful information hidden in historical memory is stronger than ANN. However, given enough historical information ANN can achieve a similar accuracy, compared with LSTM. This study provides a unique demonstration that Cryptocurrency market price is predictable. However, the explanation of the predictability could vary depending on the nature of the involved machine-learning model.
The article presents the results of a study of the theoretical foundations of the Blockchain technology. The analysis of the organization structure of its units and the principles of the system. Algorithms of smart contracts are considered and their advantages and disadvantages are analyzed. The purpose of the study is that based on the analysis of the theoretical foundations of building systems using blockchain technology and introducing them into various areas, to propose a system model using smart contracts on the Etherium platform for use in the workflow system in institutions of higher education. Convenient web interfaces for managing the creation of a contract and a module for the interaction of smart contracts with a Web application have been developed. The management of an institution of higher education, namely, a department, faculty or institute, involves the correct and timely preparation of various documentation, in which the documentation on student learning outcomes holds a special place. On its basis various financial and reporting documents are being prepared. To this end, institutions of higher education are introducing workflow system and office automation systems to manage the processing of documents, as well as to organize control over the implementation of these processes. The paper proposes the introduction of a blockchain system on the Ethereum platform using smart contracts written in the Solidity language. Solidity is a tool that is used to create machine-level code that can be run on an Ethereum Virtual Machine. Solidity allows you to create and execute a smart contract without requiring centralized or trusted parties. The use of such technologies makes it possible to significantly reduce the number of paper-based information carriers and, to a significant extent, further automate the existing the workflow system in institutions of higher education. The proposed system is a part of the workflow system of institutions of higher education, which is designed to automate the process of passing documents related to taking into account and submitting to the dean's office of the faculty or the institute the results of the final controls on academic disciplines or the results of retake of tests and exams. This process requires a large number of documents on paper. The proposed system is deployed in the local computer network of the Educational and Scientific Institute of Information Technologies and Mechatronics of Poltava National Technical Yuri Kondratyuk University and is being tested. The results allow us to draw conclusions about the reduction in the number of paper documents; time to obtain permits. In addition, the level of reliability and protection of information transmitted to the administration of the faculty or institute for further processing has increased. In the future, it is planned to introduce the proposed system for document flow automation for all institutes and faculties of the Poltava National Technical Yuri Kondratyuk University.
ABSTRACT The Ethereum block chain as a decentralized platform is so successful that many applications deployed on it. However, for the inherent transparency properties and the lack of privacy, deploying a financial application on top of it is always a challenge. In this paper, we tackle this challenge and propose an anonymous sealed-bid auction protocol based on time-released encryption atop Consortium Block chain. We adopt a strict digital certificate-based identity mechanism of the consortium block chain to permit legitimate participants, and utilize the blind signature based on elliptic curve technology to allowing anonymous participation. Moreover, a timed release public key encryption algorithm is adopted to encrypt bids and prevent auctioneer from colluding with bidders. This is completely different from the method (zero-knowledge proof) used in other papers to prevent collusion between auctioneer and bidder. We provide a specific analysis of our protocol, which shows that our protocol meets anonymity and applicability. KEYWORDS Consortium Block chain, Smart Contract, Sealed-Bid Auction, Time-Released Encryption, Blind signature
Parinya Ekparinya, Vincent Gramoli, Guillaume Jourjon
In this paper, we explore vulnerabilities and countermeasures of the recently proposed blockchain consensus based on proof-of-authority. The proof-of-work blockchains, like Bitcoin and Ethereum, have been shown both theoretically and empirically vulnerable to double spending attacks. This is why Byzantine fault tolerant consensus algorithms have gained popularity in the blockchain context for their ability to tolerate a limited number t of attackers among n participants. We formalize the recently proposed proof-of-authority consensus algorithms that are Byzantine fault tolerant by describing the Aura and Clique protocols present in the two mainstream implementations of Ethereum. We then introduce the Cloning Attack and show how to apply it to double spend in each of these protocols with a single malicious node. Our results show that the Cloning Attack against Aura is always successful while the same attack against Clique is about twice as fast and succeeds in most cases.
Sam M. Werner, Paul J. Pritz, Alexei Zamyatin, William J. Knottenbelt
Mining pools in Proof-of-Work cryptocurrencies allow miners to pool their computational resources as a means of reducing payout variance. In Ethereum, uncle blocks are valid Proof-of-Work solutions which do not become the head of the blockchain, yet yield rewards if later referenced by main chain blocks. Mining pool operators are faced with the non-trivial task of fairly distributing rewards for both block types among pool participants.
This paper reports on the development of a formal symbolic process virtual machine (FSPVM) denoted as FSPVM-E for verifying the reliability and security of Ethereum-based services at the source code level of smart contracts, and a Coq proof assistant is employed for both programming the system and for proving its correctness. The current version of FSPVM-E adopts execution-verification isomorphism, which is an application extension of Curry-Howard isomorphism, as its fundamental theoretical framework to combine symbolic execution and higher-order logic theorem proving. The four primary components of FSPVM-E include a general, extensible, and reusable formal memory framework, an extensible and universal formal intermediate programming language denoted as Lolisa, which is a large subset of the Solidity programming language using generalized algebraic datatypes, the corresponding formally verified interpreter of Lolisa, denoted as FEther, and assistant tools and libraries. The self-correctness of all components is certified in Coq. Currently, FSPVM-E supports the ERC20 token standard, and can automatically and symbolically execute Ethereum-based smart contracts, scan their standard vulnerabilities, and verify their reliability and security properties with Hoare-style logic in Coq. To the best of authors' knowledge, the present work represents the first hybrid formal verification system implemented in Coq for Ethereum smart contracts that is applied at the Solidity source code level.
In recent years, blockchains have obtained so much attention from researchers, engineers, and institutions; and the implementation of blockchains has started to revive a large number of applications ranging from e-finance, e-healthcare, smart home, Internet of Things, social security, logistics and so forth. In the literature on blockchains, it is found that most articles focused on their engineering implementation, while little attention has been devoted to the exploration of theoretical aspects of the system; however, the existing work is limited to model the mining process only. In this paper, a queuing theory-based model is proposed for understanding the working and theoretical aspects of the blockchain. We validate our proposed model using the actual statistics of two popular cryptocurrencies, Bitcoin and Ethereum, by running simulations for two months of transactions. The obtained performance measures parameters such as the Number of Transactions per block, Mining Time of Each Block, System Throughput, Memorypool count, Waiting Time in Memorypool, Number of Unconfirmed Transactions in the Whole System, Total Number of Transactions, and Number of Generated Blocks; these values are compared with actual statistics. It was found that the results gained from our proposed model are in good agreement with actual statistics. Although the simulation in this paper presents the modeling of blockchain-based cryptocurrencies only, the proposed model can be used to represent a wide range of blockchain-based systems.
Christof Ferreira Torres, Mathis Steichen, Radu State
Modern blockchains, such as Ethereum, enable the execution of so-called smart contracts - programs that are executed across a decentralised network of nodes. As smart contracts become more popular and carry more value, they become more of an interesting target for attackers. In the past few years, several smart contracts have been exploited by attackers. However, a new trend towards a more proactive approach seems to be on the rise, where attackers do not search for vulnerable contracts anymore. Instead, they try to lure their victims into traps by deploying seemingly vulnerable contracts that contain hidden traps. This new type of contracts is commonly referred to as honeypots. In this paper, we present the first systematic analysis of honeypot smart contracts, by investigating their prevalence, behaviour and impact on the Ethereum blockchain. We develop a taxonomy of honeypot techniques and use this to build HoneyBadger - a tool that employs symbolic execution and well defined heuristics to expose honeypots. We perform a large-scale analysis on more than 2 million smart contracts and show that our tool not only achieves high precision, but is also highly efficient. We identify 690 honeypot smart contracts as well as 240 victims in the wild, with an accumulated profit of more than $90,000 for the honeypot creators. Our manual validation shows that 87% of the reported contracts are indeed honeypots.
In the last year we have seen a great deal of both academic and practical
interest in the topic of vulnerabilities in smart contracts, particularly those
developed for the Ethereum blockchain. In this paper we survey the 21,270
vulnerable contracts reported by six recent academic projects. Contrary to what
might have been believed given the reported number of vulnerable contracts,
there has been precious little in terms of actual exploitation when it comes to
these vulnerabilities. We find that at most 504 out of 21,270 contracts have
been subjected to exploits. This corresponds to at most 9,066 ETH (~1.8 million
USD), or only 0.29% of the 3 million ETH (600 million USD) claimed in some of
the papers. While we are certainly not implying that smart contract
vulnerability research is without merit, our results suggest that the potential
impact of vulnerable code had been greatly exaggerated.
In recent years, we have seen a great deal of both academic and practical interest in the topic of vulnerabilities in smart contracts, particularly those developed for the Ethereum blockchain. While most of the work has focused on detecting *vulnerable* contracts, in this paper, we focus on finding how many of these vulnerable contracts have actually been *exploited*. We survey the 23,327 vulnerable contracts reported by six recent academic projects and find that, despite the amounts at stake, only 1.98% of them have been exploited since deployment. This corresponds to at most 8,487 ETH (~1.7 million USD), or only 0.27% of the 3 million ETH (600 million USD) at stake. We explain these results by demonstrating that the funds are very concentrated in a small number of contracts which are *not exploitable* in practice.
The rise of smart contract systems such as Ethereum has resulted in a proliferation of blockchain-based decentralized applications including applications that store and manage a wide range of data. Current smart contracts are designed to be executed solely by miners and are revealed entirely on-chain, resulting in reduced scalability and privacy. In this paper, we discuss that scalability and privacy of smart contracts can be enhanced by splitting a given contract into an off-chain contract and an on-chain contract. Specifically, functions of the contract that involve high-cost computation or sensitive information can be split and included as the off-chain contract, that is signed and executed by only the interested participants. The proposed approach allows the participants to reach unanimous agreement off-chain when all of them are honest, allowing computing resources of miners to be saved and content of the off-chain contract to be hidden from the public. In case of a dispute caused by any dishonest participants, a signed copy of the off-chain contract can be revealed so that a verified instance can be created to make miners enforce the true execution result. Thus, honest participants have the ability to redress and penalize any fraudulent or dishonest behavior, which incentivizes all participants to honestly follow the agreed off-chain contract. We discuss techniques for splitting a contract into a pair of on/off-chain contracts and propose a mechanism to address the challenges of handling dishonest participants in the system. Our implementation and evaluation of the proposed approach using an example smart contract demonstrate the effectiveness of the proposed approach in Ethereum.
Open access
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Blockchain Technology Applications and Security
Cryptography and Data Security
Advanced Steganography and Watermarking Techniques
Smart contracts are programs running on top of blockchain platforms. They interact with each other through well-defined interfaces to perform financial transactions in a distributed system with no trusted third parties. But these interfaces also provide a favorable setting for attackers, who can exploit security vulnerabilities in smart contracts to achieve financial gain. This paper presents SmartScopy, a system for automatic synthesis of adversarial contracts that identify and exploit vulnerabilities in a victim smart contract. Our tool explores the space of \emph{attack programs} based on the Application Binary Interface (ABI) specification of a victim smart contract in the Ethereum ecosystem. To make the synthesis tractable, we introduce \emph{summary-based symbolic evaluation}, which significantly reduces the number of instructions that our synthesizer needs to evaluate symbolically, without compromising the precision of the vulnerability query. Building on the summary-based symbolic evaluation, SmartScopy further introduces a novel approach for partitioning the synthesis search space for parallel exploration, as well as a lightweight deduction technique that can prune infeasible candidates earlier. We encoded common vulnerabilities of smart contracts in our query language, and evaluated SmartScopy on the entire data set from etherscan with $>$25K smart contracts. Our experiments demonstrate the benefits of summary-based symbolic evaluation and show that SmartScopy outperforms two state-of-the-art smart contracts analyzers, Oyente and Contractfuzz, in terms of running time, precision, and soundness. Furthermore, running on recent popular smart contracts, SmartScopy uncovers 20 vulnerable smart contracts that contain the recent BatchOverflow vulnerability and cannot be precisely detected by existing tools.
Shayan Eskandari, Seyedehmahsa Moosavi, Jeremy Clark
We consider front-running to be a course of action where an entity benefits from prior access to privileged market information about upcoming transactions and trades. Front-running has been an issue in financial instrument markets since the 1970s. With the advent of the blockchain technology, front-running has resurfaced in new forms we explore here, instigated by blockchains decentralized and transparent nature. In this paper, we draw from a scattered body of knowledge and instances of front-running across the top 25 most active decentral applications (DApps) deployed on Ethereum blockchain. Additionally, we carry out a detailed analysis of Status.im initial coin offering (ICO) and show evidence of abnormal miners behavior indicative of front-running token purchases. Finally, we map the proposed solutions to front-running into useful categories.
A decentralized application (dapp for short) refers to an application that is executed by multiple users over a decentralized network. In recent years, the number of dapp keeps fast growing, mainly due to the popularity of blockchain technology. Despite the increasing importance of dapps as a typical application type that is assumed to promote the adoption of blockchain, little is known on what, how, and how well dapps are used in practice. In addition, the insightful knowledge of whether and how a traditional application can be transformed to a dapp is yet missing. To bridge the knowledge gap, this paper presents a comprehensive empirical study on an extensive dataset of 734 dapps that are collected from three popular open dapp marketplaces, i.e., ethereum, state of the dapp, and DAppRadar. We analyze the popularity of dapps, and summarize the patterns of how smart contracts are organized in a dapp. Based on the findings, we draw some implications to help dapp developers and users better understand and deploy dapps.
Abstract Nowadays, people trade electricity through centralized companies or organizations which is vulnerable to cyber attacks and incapable of coping with increasing demands from stakeholders. In this paper, we propose a new Peer-to-Peer Electricity Blockchain Trading (P2PEBT) system based on the current charging and discharging schemes for electric vehicles (EV) in the smart grid to enable users to participate in the trading process. In order to cope with the current situation of the high volume of EV integration, the proof-of-Benefit (PoB) consensus primitives are proposed for P2PEBT to achieve demand response by providing incentives to balance local electricity demand in the novel blockchain system. PoB is implemented by executing the smart contracts on the Ethereum platform, and the process of achieving the maximal benefits is completed by submitting the transaction in the decentralized network. Security analysis shows that the P2PEBT system is able to manage a potential protection against up to a number of attacks. We demonstrate that the proposed system using the PoB consensus mechanism can achieve lower power fluctuation without requiring a third-party intermediary.
Supply chain traceability is one of the most promising use cases to benefit from characteristics of blockchain, such as decentralization, immutability and transparency, not required to build prior trust relationships among entities. A plethora of supply chain traceability solutions based on blockchain has been proposed recently. However, current systems are limited to tracing simple goods that have not been part of the manufacturing process. We recommend a method that allows for the traceability of manufactured goods, including their components. Products are represented using non-fungible digital tokens that are created on a blockchain for each batch of manufactured products. To create a link between a product and the components that are needed to produce it, we propose “token recipes” that define the amount of tokenized goods required for minting a new token. As input tokens are automatically and transparently consumed when creating a product token, the physical process of producing a new item out of existing components is projected onto the ledger. This ultimately leads to the complete traceability of goods, including the origin of inputs. Evaluating the performance of the system, we show that a prototypical implementation for the Ethereum Virtual Machine (EVM) scales linearly with the amount of the input and goods tracked.