Haya R. Hasan, Khaled Salah, Raja Jayaraman, Mohammed Omar · 8 authors
The rapid advancements in computing, storage, communications, and networking technologies have enabled the creation of Digital Twins (DTs). A DT is a digital representation of a real-world physical component, product, or equipment. A DT can be used for 3-D design, testing, simulation, and prototyping prior to the manufacturing of the physical component. Once a physical component is in operation, a DT can be used for configuration, monitoring, diagnostics, and prognostics. It is expected that DTs will gain significant attention in the foreseeable future, and will play a key role in Industry 4.0. However, today's approaches, systems, and technologies leveraged for the creation of DTs are mostly centralized and fall short of providing trusted data provenance, audit, and traceability. Also, data related to transactions, logs, and history are not secure or tamper-proof. In this paper, we propose a blockchain-based creation process of DTs to guarantee secure and trusted traceability, accessibility, and immutability of transactions, logs, and data provenance. Our proposed approach uses smart contracts to govern and track transactions initiated by participants involved in the creation of DTs. Our approach also employs decentralized storage of interplanetary file systems to store and share DTs data. Moreover, we present details on our system design and architecture, implementation, and algorithms. Furthermore, we provide security and cost analysis, and show how our approach fulfills the requirements of DTs process creation. We make the smart contract code for creating DTs publicly available on Github.
Peter Gonczol, Panagiota Katsikouli, Lasse Herskind, Nicola Dragoni
Since Bitcoin's debut in 2008, blockchain, the technology behind the cryptocurrency, has been gaining increasing scientific and industrial interest. Due to the technology's innate distributed and immutable features, the adoption of blockchains on supply chains is one of the most promising recent applications. In this survey, we review academic researches and implementations of distributed ledgers on supply chains. We present the current state of research on the subject and summarize the benefits and the challenges of the distributed organization and management of supply chains. Focusing on industrial practices and use cases, we discuss the technical characteristics and maturity of the various industrial projects. Our goal is to assess the applicability of blockchains in the supply chain domain and to provide a foundation for practitioners and researchers to direct their future projects towards improving the technology and its applications.
Electronic medical records can help people prevent diseases, improve cure rates, provide a significant basis for medical institutions and pharmaceutical companies, and provide legal evidence for medical negligence and medical disputes. However, the integrity and security problems of electronic medical data still intractable. In this paper, based on the ciphertext policy attribute-based encryption system and IPFS storage environment, combined with blockchain technology, we constructed an attribute-based encryption scheme for secure storage and efficient sharing of electronic medical records in IPFS storage environment. Our scheme is based on ciphertext policy attribute encryption, which effectively controls the access of electronic medical data without affecting efficient retrieval. Meanwhile, we store the encrypted electronic medical data in the decentralized InterPlanetary File System (IPFS), which not only ensures the security of the storage platform but also solves the problem of the single point of failure. Besides, we leverage the non-tamperable and traceable nature of blockchain technology to achieve secure storage and search for medical data. The security proof shows that our scheme achieves selective security for the choose keyword attacks. Performance analysis and real data set simulation experiments shows that our scheme is efficient and feasible.
Blockchain technology is found to have its applicability in almost every domain because of its advantages such as crypto-security, transparency, immutability, decentralized data network. In present times, a smart healthcare system with a blockchain data network and healthcare 4.0 processes provides transparency, easy and faster accessibility, security, efficiency, etc. Healthcare 4.0 trends include industry 4.0 processes such as the internet of things (IoT), industrial IoT (IIoT), cognitive computing, artificial intelligence, cloud computing, fog computing, edge computing, etc. The goal of this work is to design a smart healthcare system and it is found to be possible through integration and interoperability of Blockchain 3.0 and Healthcare 4.0 in consideration with healthcare ground-realities. Here, healthcare 4.0 processes used for data accessibility are targeted to be validated through statistical simulation-optimization methods and algorithms. The blockchain is implemented in the Ethereum network, and with associated programming languages, tools, and techniques such as solidity, web3.js, Athena, etc. Further, this work prepares a comparative and comprehensive survey of state-of-the-art blockchain-based smart healthcare systems. The comprehensive survey includes methodology, applications, requirements, outcomes, future directions, etc. A list of groups, organizations, and enterprises are prepared that are working in electronic health records (EHR), electronic medical records (EMR) or electronic personal records (EPR) mainly, and a comparative analysis is drawn concerning adopting the blockchain technology in their processes. This work has explored optimization algorithms applicable to Healthcare 4.0 trends and improves the performance of blockchain-based decentralized applications for the smart healthcare system. Further, smart contracts and their designs are prepared for the proposed system to expedite the trust-building and payment systems. This work has considered simulation and implementation to validate the proposed approach. Simulation results show that the Gas value required (indicating block size and expenditure) lies within current Etherum network Gas limits. The proposed system is active because block utilization lies above 80%. Automated smart contract execution is below 20 seconds. A good number (average 3 per simulation time) is generated in the network that indicates a health competition. Although there is error observed in simulation and implementation that lies between 0.55% and 4.24%, these errors are not affecting overall system performance because simulated and actual (taken in state-of-the-art) data variations are negligible.
We present Value Token Transfer Protocol (VTTP), a decentralized finance protocol for exchange of value or tokens within and between participating blockchain networks, fiat bank accounts and fiat wallets. The protocol allows intra-chain or inter-chain transfers of cryptocurrencies or tokens. VTTP works in both client-server and peer-to-peer models. The protocol comprises receiving from a client a transfer request to transfer value in a form of a cryptocurrency or a token, determining if the transfer request is intra-chain or inter-chain, transmitting to the client a response to the transfer request, the response comprising a raw transaction, receiving from the client a response to the raw transaction wherein a private key of a user is used to sign the raw transaction, defining a signed transaction, verifying a signature of the signed transaction and broadcasting the signed transaction to the sending and receiving blockchain networks.
This paper compares mathematical models for automated market makers including logarithmic market scoring rule (LMSR), liquidity sensitive LMSR (LS-LMSR), constant product/mean/sum, and others. It is shown that though LMSR may not be a good model for Decentralized Finance (DeFi) applications, LS-LMSR has several advantages over constant product/mean based automated market makers. However, LS-LMSR requires complicated computation (i.e., logarithm and exponentiation) and the cost function curve is concave. In certain DeFi applications, it is preferred to have computationally efficient cost functions with convex curves to conform with the principle of supply and demand. This paper proposes and analyzes constant circle/ellipse based cost functions for automated market makers. The proposed cost functions are computationally efficient (only requires multiplication and square root calculation) and have several advantages over widely deployed constant product cost functions. For example, the proposed market makers are more robust against front-runner (slippage) attacks.
Dirk Andreas Zetzsche, Douglas W. Arner, Ross P. Buckley
The emergence of Decentralized Finance (DeFi) signifies a paradigm shift in the financial sector, introducing both unparalleled opportunities and multifaceted challenges. As DeFi continues to redefine traditional financial systems, it becomes vital for stakeholders to grasp the nuances underpinning this evolution, especially the roles of behavioral finance and public policy. This article presents a literature review on financial market regulation, examining the transformative potential of DeFi and its inherent risks, and explores the implications for regulatory frameworks based on behavioral finance. Public policy in the context of DeFi is a delicate balancing act. On one hand, there's the need to protect investors and ensure market integrity. On the other, there's the risk of over-regulating and stifling the very innovations that make DeFi transformative. Policymakers must grapple with these challenges, seeking ways to create regulatory frameworks that are both protective and adaptive. In addressing the question of how to sensibly regulate financial markets in the age of DeFi, the answer may be both straightforward and somewhat counterintuitive: Regulate peers. In a decentralized system where traditional service providers play a diminished role, peers or individual participants may take on functions that are analogous to those of traditional financial operators. Therefore, these peers may find themselves subject to financial market regulations, trade law, tax law, and other applicable statutes, depending on the services they provide, much like platform operators and their obligations.
Multiple-operators (multi-OPs) spectrum sharing mechanism can effectively improve the spectrum utilization in fifth-generation (5G) wireless communication networks. The secondary users are introduced to opportunistically access the licensed spectrum of idle operators (OPs). However, the identity privacy and data security issues raise great concerns about the secure spectrum sharing among multi-OPs. To address these challenges, a permissioned blockchain trust framework is proposed for the spectrum sharing in multi-OPs wireless communication networks in this paper. The Multi-OPs Spectrum Sharing (MOSS) smart contract is designed on the constructed permissioned blockchain to implement the spectrum trading among multi-OPs. Without the need of trustless spectrum broker, the MOSS smart contract enforces multi-OPs to share the spectrum truthfully and designs a punishment mechanism to punish malicious OPs. The MOSS smart contract is tested on the Remix integrated development environment (IDE) and the gas costs of MOSS smart contract is estimated. The performance analysis of the proposed permissioned blockchain trust framework demonstrates that the privacy, openness and fairness of the proposed solution are better than traditional spectrum allocation solutions.
Gang Tian, Qibo Wang, Yi Zhao, Lantian Guo · 6 authors
With the number of smart contracts growing rapidly, retrieving the relevant smart contracts quickly and accurately has become an important issue. A key step for recognizing the related smart contracts is able to classify them accurately. Different from traditional text, the smart contract is composed of several parts: source code, code comments and other useful information like account information. How to make good use of those different kinds of features for effective classification is a problem need to be solved. Inspired by this, we proposed a smart contract classification approach based on Bi-LSTM model and Gaussian LDA, which can use a variety of information as inputs of the model, including source code, comments, tags, account and other content information. Bi-LSTM is utilized to capture grammar rules and context information in source code, while Gaussian LDA model is employed to generate comments feature where the semantics of the comments are enriched by embeddings. We also use attention mechanism to focus on the more relevant features in smart contracts for tags and fuse account information to provide additional information for classification. The experimental results show that the classification performance of the proposed model is superior to other baseline models.
Manaf Zghaibeh, Umer Farooq, Najam Ul Hasan, Imran Baig
Governments rely on collected data to analyze their citizens' health requirements and needs. Such data is usually of scattered manner gathered by several agencies and entities that fall under different business models and goals. Hence, the scattered nature of this data creates a burden on governments in precisely planning adequate health bills that guarantee the wellbeing of their citizens. Furthermore, the issue of synchronizing and having a real-time access to such data exacerbates the problem even more. Therefore, a system that guarantees the integrity, accessibility, correctness and security of medical data in a highly synchronized environment is crucial for governments to accurately project their future needs. In this paper, we present Smart-Health (SHealth), a blockchain-based health management system. In its crux, SHealth is a private multi-layered blockchain integrated with a multi-tiered addressing scheme that defines the privileges and permissions of entities in the system. Blockchain-based systems assure security, reliability, availability, resistance against tampering and malicious attacks, seamless integration, and easy data management. SHealth proposes a complete autonomy to its users. Through a user-friendly graphical interface it capitalizes on smart contracts to initiate various requests and inquiries pertaining to patients such as appointments, medical tests, medications, medical procedures, or history. SHealth is simple, robust, efficient, secured, and completely automated. All the stakeholders in the system can access the health related data stored in a distributed database without compromising its authenticity. SHealth covers all the possible scenarios in health systems from which some of them are explained in this work.
Bin Yu, Ping Zhan, Ming Lei, Fang Zhou · 5 authors
Currently, food quality has become a major concern for the food industry. To efficiently detect food quality problems during the production process, food enterprises must build quality monitoring systems. However, in a traditional quality monitoring system, data tampering and centralized storage have become barriers to reliability. In addition, due to lack of sufficient automation, traditional quality monitoring approaches are usually inefficient. Fortunately, blockchain is a promising technology that is tamper-proof and decentralized. Moreover, smart contracts, which are executable codes on the blockchain platform, are able to conduct transactions between mutually untrusted parties and are self-executing and self-verifying. By combining smart contracts and quality evaluation models, this paper presents an intelligent quality monitoring system for fruit juice production. This system has the characteristics of high automation and high reliability. In this system, response surface models are established based on preproduction data, and the optimal production condition for each stage is identified. During the actual production process, smart contracts are executed to record production data on a blockchain. These data serve as the inputs for evaluation models. Based on the evaluation outcome, smart contracts will decide whether the production process can be resumed or not. To evaluate the feasibility of the presented system, a prototype version of the quality monitoring system for flat peach juice production is implemented based on the Ethereum platform and executed in the Remix IDE.
Ilhaam A. Omar, Raja Jayaraman, Khaled Salah, Mazin Debe · 5 authors
Supply chain networks have grown in complexity and size due to increased globalization leading to a variety of challenges and opportunities for improvement. Optimizing inventory levels and adjusting replenishment policies have significant effects on the operational performance and profitability of supply chains. Vendor Managed Inventory (VMI) is a mutually beneficial arrangement between supplier and buyer, where the supplier is responsible for making inventory and replenishment decisions based on buyers' inventory status. Potential benefits of VMI include reducing inventories, enabling information sharing, eliminating safety stock, and reducing purchasing related costs across the supply chain. In today's supply chains, VMI operations face critical challenges related to data integrity, transparency, traceability, and single point of failure due to its centralized architecture. Blockchain technology is a distributed ledger that ensures a transparent, safe, and secure exchange of data among supply chain stakeholders. The advantages of adopting blockchain technology for VMI operations in a supply chain include decentralized control, security, traceability, and auditable time-stamped transactions. In this paper, we present a blockchain-based approach using smart contracts to transform VMI supply chain operations. We propose a generic framework using Ethereum smart contracts and decentralized storage systems to automate the processes and information exchange and detailed algorithms that capture the interactions among supply chain stakeholders. The smart contract code was developed and tested in Remix environment. We present cost and security analysis incurred by the stakeholders in the supply chain. Adopting a blockchain-based solution to VMI operations in supply chains is economically viable and provides a streamlined, secure, trusted, and transparent mode of communication among various stakeholders.
Victor Youdom Kemmoe, W. H. Stone, Jeehyeong Kim, Daeyoung Kim · 5 authors
Smart contracts, as an added functionality to blockchain, have received increased attention recently. They are executable programs whose instance and state are stored in blockchain. Hence, smart contracts and blockchain enable a trustable, trackable, and irreversible protocol without the need for trusted third parties which generally constitute a single point of failure. If a user creates and distributes a smart contract, others will be able to interact with it while the underlying blockchain ensures a trustable execution. In this paper, we aim to introduce state-of-the-art technologies of the smart contract protocol. We firstly introduce the history of blockchain and smart contracts followed by their step-by-step operations. Then, we introduce the survey results which are classified into four categories based on their purposes: cryptography, access management, social application, and smart contract structure. By presenting the most recent knowledge, this paper will contribute to the advances and proliferation of smart contracts.
Serkan Seven, Gang Yao, Ahmet Soran, Ahmet Önen · 5 authors
A novel Peer-to-peer (P2P) energy trading scheme for a Virtual Power Plant (VPP) is proposed by using Smart Contracts on Ethereum Blockchain Platform. The P2P energy trading is the recent trend the power society is keen to adopt carrying out several trial projects as it eases to generate and share the renewable energy sources in a distributed manner inside local community. Blockchain and smart contracts are the up-and-coming phenomena in the scene of the information technology used to be considered as the cutting-edge research topics in power systems. Earlier works on P2P energy trading including and excluding blockchain technology were focused mainly on the optimization algorithm, Information and Communication Technology, and Internet of Things. Therefore, the financial aspects of P2P trading in a VPP framework is focused and in that regard a P2P energy trading mechanism and bidding platform are developed. The proposed scheme is based on public blockchain network and auction is operated by smart contract addressing both cost and security concerns. The smart contract implementation and execution in a VPP framework including bidding, withdrawal, and control modules developments are the salient feature of this work. The proposed architecture is validated using realistic data with the Ethereum Virtual Machine (EVM) environment of Ropsten Test Network.
Applications of Blockchain (BC) technology and Cyber-Physical Systems (CPS) are increasing exponentially. However, framing resilient and correct smart contracts (SCs) for these smart application is a quite challenging task because of the complexity associated with them. SC is modernizing the traditional industrial, technical, and business processes. It is self-executable, self-verifiable, and embedded into the BC that eliminates the need for trusted third-party systems, which ultimately saves administration as well as service costs. It also improves system efficiency and reduces the associated security risks. However, SCs are well encouraging the new technological reforms in Industry 4.0, but still, various security and privacy challenges need to be addressed. In this paper, a survey on SC security vulnerabilities in the software code that can be easily hacked by a malicious user or may compromise the entire BC network is presented. As per the literature, the challenges related to SC security and privacy are not explored much by the authors around the world. From the existing proposals, it has been observed that designing a complex SCs cannot mitigate its privacy and security issues. So, this paper investigates various Artificial Intelligence (AI) techniques and tools for SC privacy protection. Then, open issues and challenges for AI-based SC are analyzed. Finally, a case study of retail marketing is presented, which uses AI and SC to preserve its security and privacy.
In the last decade, smart contract security issues lead to tremendous losses, which has attracted increasing public attention both in industry and in academia. Researchers have embarked on efforts with logic rules, symbolic analysis, and formal analysis to achieve encouraging results in smart contract vulnerability detection tasks. However, the existing detection tools are far from satisfactory. In this paper, we attempt to utilize the deep learning-based approach, namely bidirectional long-short term memory with attention mechanism (BLSTM-ATT), aiming to precisely detect reentrancy bugs. Furthermore, we propose contract snippet representations for smart contracts, which contributes to capturing essential semantic information and control flow dependencies. Our extensive experimental studies on over 42,000 real-world smart contracts show that our proposed model and contract snippet representations significantly outperform state-of-the-art methods. In addition, this work proves that it is practical to apply deep learning-based technology on smart contract vulnerability detection, which is able to promote future research towards this area.
Smart contracts are programs that reside within decentralized blockchains and are executed pursuant to triggered instructions. A smart contract acts in a similar way to a traditional agreement but negates the necessity for the involvement of a third party. Smart contracts are capable of initiating their commands automatically, thus eliminating the involvement of a regulatory body. As a consequence of blockchain's immutable feature, smart contracts are developed in a manner that is distinct from traditional software. Once deployed to the blockchain, a smart contract cannot be modified or updated for security patches, thus encouraging developers to implement strong security strategies before deployment in order to avoid potential exploitation at a later time. However, the most recent dreadful attacks and the multifarious existing vulnerabilities which result as a consequence of the absence of security patches have challenged the sustainability of this technology. Attacks such as the Decentralized Autonomous Organization (DAO) attack and the Parity Wallet hack have cost millions of dollars simply as a consequence of naïve bugs in the smart contract code. In this paper, we classify blockchain exploitation techniques into 4 categories based on the attack rationale; attacking consensus protocols, bugs in the smart contract, malware running in the operating system, and fraudulent users. We then focus on smart contract vulnerabilities, analyzing the 7 most important attack techniques to determine the real impact on smart contract technology. We reveal that even adopting the 10 most widely used tools to detect smart contract vulnerabilities, these still contain known vulnerabilities, providing a dangerously false sense of security. We conclude the paper with a discussion about recommendations and future research lines to progress towards a secure smart contract solution.
We investigate the puzzle of widespread participation in cryptocurrency pump-and-dump manipulation schemes. Unlike stock market manipulators, cryptocurrency manipulators openly declare their intentions to pump specific coins, rather than trying to deceive investors. Puzzlingly, people join in despite negative expected returns. In a simple framework, we demonstrate how overconfidence and gambling preferences can explain participation in these schemes. Analyzing a sample of 355 cases in 6 months, we find strong empirical support for both mechanisms. Pumps generate extreme price distortions of 65% on average, abnormal trading volumes in the millions of dollars, and large wealth transfers between participants.
Pairs trading is a strategy based on exploiting mean reversion in prices of securities. Even though these strategies have been shown to perform well for equities, their performance is unknown for the field of cryptocurrencies, usually perceived as inefficient and predictable. We apply the distance and cointegration methods to a basket of 26 liquid cryptocurrencies traded on the Binance exchange, specifically at 5-minute, 1-hour and daily frequencies. In our backtests, the strategies underperform classical benchmarks. However, the results are quite sensitive to parameter settings and external factors such as transaction costs or execution windows. Higher-frequency trading delivers significantly better performance, and while the most common daily distance method returns -0.07% monthly, this increases to 11.61% monthly for 5-minute frequency. Additionally, we find evidence of simple mean-reverting behavior in intraday prices that is missing in daily data, and which provides further support for the inefficiency of cryptocurrency markets.