Blockchain-based reputation models for e-commerce: a systematic literature review

The Digital Age is the present, and nobody can deny that. With it has come a digital transformation in various sectors of activity, and e-commerce is no exception. Over the last few decades, there has been a massive increase in its utilization rates, as it has several advantages over traditional commerce. At the same time, the rise in the number of crimes on the Internet and, consequently, the understanding of the risks involved in online shopping has led consumers to become more cautious, looking for information about the seller and taking it into account when making a purchase decision. The need to get to know the merchant better before making a purchase decision has encouraged the creation of reputation systems, whose services play an essential role in today's e-commerce context. Reputation systems act as mechanisms to reduce information asymmetry between consumers and sellers and establish rankings that attest to fulfilling standards and policies considered necessary for shops operating in the digital market. The critical problems in current reputation systems are the frauds and attacks that such systems currently have to deal with, which results in a lack of trust between users. These security and fraud issues are critical because users' trust is commonly based on reputation models, and many of these current systems are not immune to them, thus compromising e-commerce growth. The need for a better and safer model emerges with the development of e-commerce. Through reading the articles and pursuing the answers to the primary questions, blockchain is data register technology to be analysed in order to gain a better acknowledgment of the potential of such technology. More research work and investigation must be done to fully understand how to create a more assertive reputation model. Thus, this study systematizes the knowledge generated by reputation models in E-commerce studies in Scopus, WoS databases, and Google Scholar, using PRISMA methodology. A systematic approach was adopted in conducting a literature review. The need for a systematic literature review came from the knowledge that there are reputation systems that mitigate some of the problems. In addition to identifying some indicators used in reputation models, we also conclude that these models could help provide some insurance to buyers and sellers, with a commitment to being a problem solver, being able to mitigate known problems such as Collusion, Sybil attacks, laundering attacks, and preventing online fraud ranging from ballot stuffing and bad-mouthing. Nevertheless, the results of the present work demonstrate that even though these reputation models still cannot solve all of the problems, attacking one fraud opens the door to an attack. The architecture of the models was identified, with the realization that a few lacks that need to be fulfilled

Securing IoT Applications through Decentralised and Distributed IoT-Blockchain Architectures

The integration of blockchain into IoT can provide reliable control of the IoT network's ability to distribute computation over a large number of devices. It also allows the AI system to use trusted data for analysis and forecasts while utilising the available IoT hardware to coordinate the execution of tasks in parallel, using a fully distributed approach. This thesis's  rst contribution is a practical implementation of a real world IoT- blockchain application, ood detection use case, is demonstrated using Ethereum proof of authority (PoA). This includes performance measurements of the transaction con-  rmation time, the system end-to-end latency, and the average power consumption. The study showed that blockchain can be integrated into IoT applications, and that Ethereum PoA can be used within IoT for permissioned implementation. This can be achieved while the average energy consumption of running the ood detection system including the Ethereum Geth client is small (around 0.3J). The second contribution is a novel IoT-centric consensus protocol called honesty- based distributed proof of authority (HDPoA) via scalable work. HDPoA was analysed and then deployed and tested. Performance measurements and evaluation along with the security analyses of HDPoA were conducted using a total of 30 di erent IoT de- vices comprising Raspberry Pis, ESP32, and ESP8266 devices. These measurements included energy consumption, the devices' hash power, and the transaction con rma- tion time. The measured values of hash per joule (h/J) for mining were 13.8Kh/J, 54Kh/J, and 22.4Kh/J when using the Raspberry Pi, the ESP32 devices, and the ESP8266 devices, respectively, this achieved while there is limited impact on each de- vice's power. In HDPoA the transaction con rmation time was reduced to only one block compared to up to six blocks in bitcoin. The third contribution is a novel, secure, distributed and decentralised architecture for supporting the implementation of distributed arti cial intelligence (DAI) using hardware platforms provided by IoT. A trained DAI system was implemented over the IoT, where each IoT device hosts one or more neurons within the DAI layers. This is accomplished through the utilisation of blockchain technology that allows trusted interaction and information exchange between distributed neurons. Three di erent datasets were tested and the system achieved a similar accuracy as when testing on a standalone system; both achieved accuracies of 92%-98%. The system accomplished that while ensuring an overall latency of as low as two minutes. This showed the secure architecture capabilities of facilitating the implementation of DAI within IoT while ensuring the accuracy of the system is preserved. The fourth contribution is a novel and secure architecture that integrates the ad- vantages o ered by edge computing, arti cial intelligence (AI), IoT end-devices, and blockchain. This new architecture has the ability to monitor the environment, collect data, analyse it, process it using an AI-expert engine, provide predictions and action- able outcomes, and  nally share it on a public blockchain platform. The pandemic caused by the wide and rapid spread of the novel coronavirus COVID-19 was used as a use-case implementation to test and evaluate the proposed system. While providing the AI-engine trusted data, the system achieved an accuracy of 95%,. This is achieved while the AI-engine only requires a 7% increase in power consumption. This demon- strate the system's ability to protect the data and support the AI system, and improves the IoT overall security with limited impact on the IoT devices. The  fth and  nal contribution is enhancing the security of the HDPoA through the integration of a hardware secure module (HSM) and a hardware wallet (HW). A performance evaluation regarding the energy consumption of nodes that are equipped with HSM and HW and a security analysis were conducted. In addition to enhancing the nodes' security, the HSM can be used to sign more than 120 bytes/joule and encrypt up to 100 bytes/joule, while the HW can be used to sign up to 90 bytes/joule and encrypt up to 80 bytes/joule. The result and analyses demonstrated that the HSM and HW enhance the security of HDPoA, and also can be utilised within IoT-blockchain applications while providing much needed security in terms of con dentiality, trust in devices, and attack deterrence. The above contributions showed that blockchain can be integrated into IoT systems. It showed that blockchain can successfully support the integration of other technolo- gies such as AI, IoT end devices, and edge computing into one system thus allowing organisations and users to bene t greatly from a resilient, distributed, decentralised, self-managed, robust, and secure systems

Blockchain-Coordinated Frameworks for Scalable and Secure Supply Chain Networks

Supply chains have progressed through time from being limited to a few regional traders to becoming complicated business networks. As a result, supply chain management systems now rely significantly on the digital revolution for the privacy and security of data. Due to key qualities of blockchain, such as transparency, immutability and decentralization, it has recently gained a lot of interest as a way to solve security, privacy and scalability problems in supply chains. However conventional blockchains are not appropriate for supply chain ecosystems because they are computationally costly, have a limited potential to scale and fail to provide trust. Consequently, due to limitations with a lack of trust and coordination, supply chains tend to fail to foster trust among the network’s participants. Assuring data privacy in a supply chain ecosystem is another challenge. If information is being shared with a large number of participants without establishing data privacy, access control risks arise in the network. Protecting data privacy is a concern when sending corporate data, including locations, manufacturing supplies and demand information. The third challenge in supply chain management is scalability, which continues to be a significant barrier to adoption. As the amount of transactions in a supply chain tends to increase along with the number of nodes in a network. So scalability is essential for blockchain adoption in supply chain networks. This thesis seeks to address the challenges of privacy, scalability and trust by providing frameworks for how to effectively combine blockchains with supply chains. This thesis makes four novel contributions. It first develops a blockchain-based framework with Attribute-Based Access Control (ABAC) model to assure data privacy by adopting a distributed framework to enable fine grained, dynamic access control management for supply chain management. To solve the data privacy challenge, AccessChain is developed. This proposed AccessChain model has two types of ledgers in the system: local and global. Local ledgers are used to store business contracts between stakeholders and the ABAC model management, whereas the global ledger is used to record transaction data. AccessChain can enable decentralized, fine-grained and dynamic access control management in SCM when combined with the ABAC model and blockchain technology (BCT). The framework enables a systematic approach that advantages the supply chain, and the experiments yield convincing results. Furthermore, the results of performance monitoring shows that AccessChain’s response time with four local ledgers is acceptable, and therefore it provides significantly greater scalability. Next, a framework for reducing the bullwhip effect (BWE) in SCM is proposed. The framework also focuses on combining data visibility with trust. BWE is first observed in SC and then a blockchain architecture design is used to minimize it. Full sharing of demand data has been shown to help improve the robustness of overall performance in a multiechelon SC environment, especially for BWE mitigation and cumulative cost reduction. It is observed that when it comes to providing access to data, information sharing using a blockchain has some obvious benefits in a supply chain. Furthermore, when data sharing is distributed, parties in the supply chain will have fair access to other parties’ data, even though they are farther downstream. Sharing customer demand is important in a supply chain to enhance decision-making, reduce costs and promote the final end product. This work also explores the ability of BCT as a solution in a distributed ledger approach to create a trust-enhanced environment where trust is established so that stakeholders can share their information effectively. To provide visibility and coordination along with a blockchain consensus process, a new consensus algorithm, namely Reputation-based proof-of cooperation (RPoC), is proposed for blockchain-based SCM, which does not involve validators to solve any mathematical puzzle before storing a new block. The RPoC algorithm is an efficient and scalable consensus algorithm that selects the consensus node dynamically and permits a large number of nodes to participate in the consensus process. The algorithm decreases the workload on individual nodes while increasing consensus performance by allocating the transaction verification process to specific nodes. Through extensive theoretical analyses and experimentation, the suitability of the proposed algorithm is well grounded in terms of scalability and efficiency. The thesis concludes with a blockchain-enabled framework that addresses the issue of preserving privacy and security for an open-bid auction system. This work implements a bid management system in a private BC environment to provide a secure bidding scheme. The novelty of this framework derives from an enhanced approach for integrating BC structures by replacing the original chain structure with a tree structure. Throughout the online world, user privacy is a primary concern, because the electronic environment enables the collection of personal data. Hence a suitable cryptographic protocol for an open-bid auction atop BC is proposed. Here the primary aim is to achieve security and privacy with greater efficiency, which largely depends on the effectiveness of the encryption algorithms used by BC. Essentially this work considers Elliptic Curve Cryptography (ECC) and a dynamic cryptographic accumulator encryption algorithm to enhance security between auctioneer and bidder. The proposed e-bidding scheme and the findings from this study should foster the further growth of BC strategies

Blockchain-Based Water-Energy Transactive Management with Spatial-Temporal Uncertainties

Water resources are vital to the energy conversion process but few efforts have been devoted to the joint optimization problem which is fundamentally critical to the water-energy nexus for small-scale or remote energy systems (e.g., energy hubs). Traditional water and energy trading mechanisms depend on centralized authorities and cannot preserve security and privacy effectively. Also, their transaction process cannot be verified and is subject to easy tampering and frequent exposures to cyberattacks, forgery, and network failures. Toward that end, water-energy hubs (WEHs) offers a promising way to analyse water-energy nexus for greater resource utilization efficiency. We propose a two-stage blockchain-based transactive management method for multiple, interconnected WEHs. Our method considers peer-topeer (P2P) trading and demand response, and leverages blockchain to create a secure trading environment. It features auditing and resource transaction record management via system aggregators enabled by a consortium blockchain, and entails spatial-temporal distributionally robust optimization (DRO) for renewable generation and load uncertainties. A spatial-temporal ambiguity set is incorporated in DRO to characterize the spatial-temporal dependencies of the uncertainties in distributed renewable generation and load demand. We conduct a simulation-based evaluation that includes robust optimization and the moment-based DRO as benchmarks. The results reveal that our method is consistently more effective than both benchmarks. Key findings include i) our method reduces conservativeness with lower WEH trading and operation costs, and achieves important performance improvements by up to 6.1%; and ii) our method is efficient and requires 18.7% less computational time than the moment-based DRO. Overall, this study contributes to the extant literature by proposing a novel two-stage blockchain-based WEH transaction method, developing a realistic spatialtemporal ambiguity set to effectively hedge against the uncertainties for distributed renewable generation and load demand, and producing empirical evidence suggesting its greater effectiveness and values than several prevalent methods.</p

Blockchain-Based Water-Energy Transactive Management with Spatial-Temporal Uncertainties

Water resources are vital to the energy conversion process but few efforts have been devoted to the joint optimization problem which is fundamentally critical to the water-energy nexus for small-scale or remote energy systems (e.g., energy hubs). Traditional water and energy trading mechanisms depend on centralized authorities and cannot preserve security and privacy effectively. Also, their transaction process cannot be verified and is subject to easy tampering and frequent exposures to cyberattacks, forgery, and network failures. Toward that end, water-energy hubs (WEHs) offers a promising way to analyse water-energy nexus for greater resource utilization efficiency. We propose a two-stage blockchain-based transactive management method for multiple, interconnected WEHs. Our method considers peer-topeer (P2P) trading and demand response, and leverages blockchain to create a secure trading environment. It features auditing and resource transaction record management via system aggregators enabled by a consortium blockchain, and entails spatial-temporal distributionally robust optimization (DRO) for renewable generation and load uncertainties. A spatial-temporal ambiguity set is incorporated in DRO to characterize the spatial-temporal dependencies of the uncertainties in distributed renewable generation and load demand. We conduct a simulation-based evaluation that includes robust optimization and the moment-based DRO as benchmarks. The results reveal that our method is consistently more effective than both benchmarks. Key findings include i) our method reduces conservativeness with lower WEH trading and operation costs, and achieves important performance improvements by up to 6.1%; and ii) our method is efficient and requires 18.7% less computational time than the moment-based DRO. Overall, this study contributes to the extant literature by proposing a novel two-stage blockchain-based WEH transaction method, developing a realistic spatialtemporal ambiguity set to effectively hedge against the uncertainties for distributed renewable generation and load demand, and producing empirical evidence suggesting its greater effectiveness and values than several prevalent methods.</p

Blockchain Technology for Enhancing Supply Chain Performance and Reducing the Threats Arising from the COVID-19 Pandemic

A rigorous examination of the most recent advancements in blockchain technology (BCT) and artificial intelligence (AI)-enabled supply chain networks is provided in this book. The edited book brings together the perspectives of a number of authors who have presented their most recent views on blockchain technology and its applications in a variety of disciplines. The submitted papers contribute to a better understanding of how blockchain technology can improve the efficacy of human activities during a pandemic, improve traceability and visibility in the automotive supply chain, support food safety and reliability through digitalisation of the food supply chain, and increase the performance of next-generation digital supply chains, among other things. The book attempts to address and prepare a way to address the complicated issues that supply chains are encountering as a result of the global pandemic

Open Source Law, Policy and Practice

This book examines various policies, including the legal and commercial aspects of the Open Source phenomenon. Here, ‘Open Source’ is adopted as convenient shorthand for a collection of diverse users and communities, whose differences can be as great as their similarities. The common thread is their reliance on, and use of, law and legal mechanisms to govern the source code they write, use, and distribute. The central fact of open source is that maintaining control over source code relies on the existence and efficacy of intellectual property (‘IP’) laws, particularly copyright law. Copyright law is the primary statutory tool that achieves the end of openness, although implemented through private law arrangements at varying points within the software supply chain. This dependent relationship is itself a cause of concern for some philosophically in favour of ‘open’, with some predicting (or hoping) that the free software movement will bring about the end of copyright as a means for protecting software