Search Results (69)

In recent years, a large number of Internet of Things (IoT)-based products, solutions, and services have emerged from the industry to enter the marketplace, improving the quality of service. With the wide adoption of IoT-based systems/applications in real scenarios, the privacy preservation (PP) topic has garnered significant attention from both academia and industry; as a result, many PP solutions have been developed, tailored to IoT-based systems/applications. This paper provides an in-depth analysis of state-of-the-art (SOTA) PP solutions recently developed for IoT-based systems and applications. We delve into SOTA PP methods that preserve IoT data privacy and categorize them into two scenarios: on-device and cloud computing. We categorize the existing PP solutions into privacy-by-design (PbD), such as federated learning (FL) and split learning (SL), and privacy engineering solutions (PESs), such as differential privacy (DP) and anonymization, and we map them to IoT-driven applications/systems. We further summarize the latest SOTA methods that employ multiple PP techniques like $ϵ$-DP + anonymization or $ϵ$-DP + blockchain + FL (rather than employing just one) to preserve IoT data privacy in both PES and PbD categories. Lastly, we highlight quantum-based methods devised to enhance the security and/or privacy of IoT data in real-world scenarios. We discuss the status of current research in PP techniques for IoT data within the scope established for this paper, along with opportunities for further research and development. To the best of our knowledge, this is the first work that provides comprehensive knowledge about PP topics centered on the IoT, and which can provide a solid foundation for future research. Full article

Against the backdrop of the increasingly salient constraints of resource scarcity and environmental pressures on global economic development, sustainable innovation emerges as an imperative strategic pathway for corporations to secure a competitive edge in the international marketplace. Corporate innovation capability serves as the critical factor for both the advancement of sustainable innovation and the maintenance of the corporate competitive edge. While the extant literature has extensively explored how internal and external governance mechanism forces shape corporate investment decision-making, the critical role of non-CEO executives in the process of corporate innovation investment decision-making remains conspicuously underexplored. This study examines the effect of bottom–up governance mechanisms within executive teams on corporate innovation investment from the perspective of non-CEO executive independence. We used a sample of A-listed companies on the Shanghai and Shenzhen stock exchanges from 2007 to 2021 for empirical tests. We found a U-shaped relation between non-CEO executive independence and corporate innovation investment, and this finding still held after addressing endogeneity issues and conducting a series of robustness tests. Mechanism analysis revealed that both non-CEO executives’ decision horizon and firm agency costs positively moderate this U-shaped relationship. This U-shaped effect is pronounced in firms with lower CEO power, lower levels of corporate governance, and non-state-owned firms. Our findings provide an important basis for clarifying the internal governance mechanism of the executive teams while offering new insights for optimizing the allocation of corporate resources and promoting corporate innovation from the perspective of improving corporate governance. Full article

This paper presents a secure 5G offloading mechanism leveraging Blockchain technology and Self-Sovereign Identity (SSI). The advent of 5G has significantly enhanced the capabilities of all sectors, enabling innovative applications and improving security and efficiency. However, challenges such as limited infrastructure, signal interference, and high upgrade costs persist. Offloading processes already address these issues but they require more transparency and security. This paper proposes a Blockchain-based marketplace using Hyperledger Fabric to optimize resource allocation and enhance security. This marketplace facilitates the exchange of services and resources among operators, promoting competition and flexibility. Additionally, the paper introduces an SSI-based authentication system to ensure privacy and security during the offloading process. The architecture and components of the marketplace and authentication system are detailed, along with their data models and operations. Performance evaluations indicate that the proposed solutions do not significantly degrade offloading times, making them suitable for everyday applications. As a result, the integration of Blockchain and SSI technologies enhances the security and efficiency of 5G offloading. Full article

The global energy sector is rapidly changing due to decentralization, renewable energy integration, and digitalization, challenging traditional energy business models. This paper explores a startup concept for an AI-assisted regional marketplace for renewable energy, specifically suited for small- and medium-sized enterprises (SMEs). Driven by advancements in artificial intelligence (AI), big data, and Internet of Things (IoT) technology, this marketplace enables efficient energy trading through real-time supply–demand matching with dynamic pricing. Decentralized energy systems, such as solar and wind power, offer benefits like enhanced energy security but also present challenges in balancing supply and demand due to volatility. This research develops and validates an AI-based pricing model to optimize regional energy consumption and incentivize efficient usage to support grid stability. Through a SWOT analysis, this study highlights the strengths, weaknesses, opportunities, and threats of such a platform. Findings indicate that, with scalability, the AI-driven marketplace could significantly support the energy transition by increasing renewable energy use and therefore reducing carbon emissions. This paper presents a viable, scalable solution for SMEs aiming to participate in a resilient, sustainable, and localized energy market. Full article

This article provides an in-depth analysis of blockchain research in the energy sector, focusing on projects funded by the U.S. Department of Energy (DOE) and comparing them with industry-funded initiatives. A total of 110 funded activities within the U.S. power industry were successfully tracked and mapped into a newly developed categorization framework. This framework is designed to help research agencies to systematically understand their funded portfolio. Such characterization is expected to help them make effective investments, identify research gaps, measure impact, and advance technological progress to meet national goals. In line with this need, the proposed framework proposes a 2-D categorization matrix to systematically classify blockchain efforts within the energy sector.Under the proposed framework, the Energy System Domain serves as the primary classification dimension, categorizing use cases into 30 distinct applications. The second dimension, Blockchain Properties, captures the specific needs and functionalities provided by Blockchain technology. The aim was to capture blockchain’s applicability and functionality: where and why blockchain? Principles behind the selection of the viewpoint dimensions were carefully defined based on consensus obtained through the Blockchain for Optimized Security and Energy Management (BLOSEM) project. The mapped results show that activities within the Grid Automation, Coordination, and Control (31.8%), Marketplaces and Trading (25.5%), Foundational Blockchain Research (19.1%), and Supply Chain Management (17.3%) domains have been actively pursued to date. The three leading specific use case applications were identified as Transactive Energy Management for Marketplaces and Trading, Asset Management for Supply Chain Management, and Fundamental Blockchain for Foundational Blockchain Research. The Marketplaces and Trading and Retail Services Enablement domains stood out as being favored by industry by a factor greater than 2 (2.3 and 2.6, respectively), yet there seemed to be little to zero investment from DOE. Approximately 76% of the total projects prioritized Immutability, Identity Management, and Decentralization and/or Disintermediation compared to Asset Digitization and/or Tokenization, Automation, and Privacy and/or Anonymity. The greatest discrepancies between DOE and industry were in Asset Digitization and/or Tokenization and Automation. The industry efforts (36% in Asset Digitization/Tokenization and 22% in Automation) was 14 times and 2.4 times, respectively, more intensive than the DOE-sponsored efforts, indicating a significant discrepancy in industry versus government priorities. Overall, quantifying DOE-sponsored projects and industry activities through mapping provides clarity on portfolio investments and opportunities for future research. Full article

The maintenance of plant germplasm and its genetic diversity is critical to preserving and making it available for food security, so this invaluable diversity is not permanently lost due to population growth and development, climate change, or changing needs from the growers and/or the marketplace. There are numerous genebanks worldwide that serve to preserve valuable plant germplasm for humankind’s future and to serve as a resource for research, breeding, and training. The United States Department of Agriculture (USDA) National Plant Germplasm System (NPGS) and the Consultative Group for International Agricultural Research (CGIAR) both have a network of plant germplasm collections scattered across varying geographical locations preserving genetic resources for the future. Besides the USDA and CGIAR, there are germplasm collections established in many countries across the world that also aim to preserve crop and plant collections. Due to the advancement of technology, genotyping and sequencing whole genomes of plant germplasm collections is now feasible. Data from genotyping can help define genetic diversity within a collection, identify genetic gaps, reveal genetic redundancies and verify uniqueness, enable the comparison of collections of the same crop across genebanks (rationalization), and determine errors or mix-ups in genetic identity that may have occurred in a germplasm collection. Large-scale projects, such as genotyping germplasm collections, require strategic planning and the development of best practices. This article details strategies and best practices to consider when genotyping whole collections, considerations for the identity verification of germplasm and determining genetic replicates, quality management systems (QMS)/QC genotyping, and some use cases. Full article

The rapid advancement and widespread adoption of artificial intelligence (AI) across diverse industries, including healthcare, finance, manufacturing, and retail, underscore the transformative potential of AI technologies. This necessitates the development of viable AI model marketplaces that facilitate the development, trading, and sharing of AI models across the pervasive industrial domains to harness and streamline their daily activities. These marketplaces act as centralized hubs, enabling stakeholders such as developers, data owners, brokers, and buyers to collaborate and exchange resources seamlessly. However, existing AI marketplaces often fail to address the demands of modern and next-generation application domains. Limitations in pricing models, standardization, and transparency hinder their efficiency, leading to a lack of scalability and user adoption. This paper aims to target researchers, industry professionals, and policymakers involved in AI development and deployment, providing actionable insights for designing robust, secure, and transparent AI marketplaces. By examining the evolving landscape of AI marketplaces, this paper identifies critical gaps in current practices, such as inadequate pricing schemes, insufficient standardization, and fragmented policy enforcement mechanisms. It further explores the AI model life-cycle, highlighting pricing, trading, tracking, security, and compliance challenges. This detailed analysis is intended for an audience with a foundational understanding of AI systems, marketplaces, and their operational ecosystems. The findings aim to inform stakeholders about the pressing need for innovation and customization in AI marketplaces while emphasizing the importance of balancing efficiency, security, and trust. This paper serves as a blueprint for the development of next-generation AI marketplaces that meet the demands of both current and future application domains, ensuring sustainable growth and widespread adoption. Full article

Nowadays, the increase in sustainable investments, especially when it comes to energy efficiency in buildings, has been recognised as an important pillar towards reductions in energy consumption. In this context, there is a need for efficient and user-friendly digital tools that can support decision-making procedures for all involved parties in the energy efficiency value chain. The scope of this paper is to present a high-level architecture and system design of the energy efficiency marketplace developed within the framework of the ENERGATE project, an EU-funded initiative aiming to assist Building Owners, Project Implementors, and Financial Institutions to collaborate and execute energy-efficient building renovations. To this end, structured data through predefined information entries will be collected. This will facilitate the interactions between heterogenous stakeholders and contribute to the standardisation of processes. The paper focuses on the functional description of the system design of the ENERGATE platform by defining the architecture, components, modules, interfaces, and structured data, as well as highlighting the requirements of potential platform users and design principles to meet the necessary requirements while ensuring security, reliability, and effectiveness. Full article

Global supply chains, especially in commodity trading, are plagued by fragmentation, lack of transparency, and trust deficits among participants. These issues lead to inefficiencies, increased costs, and an over-reliance on intermediaries. The present Communication describes a blockchain-based platform that leverages Self-Sovereign Identity (SSI) and Verifiable Credentials (VCs) to address these challenges in supply chain management. Developed in collaboration with coffee industry stakeholders, our approach proposes a platform with an integrated marketplace for seller discovery, enables precise order definition with detailed terms and conditions, and actively guides both buyers and sellers throughout the shipping process, managing financial guarantees and ensuring a secure transaction flow. The platform is compatible with both traditional banking infrastructure and modern crypto-based systems, enabling seamless financial transactions. In cases where disputes arise, we empower users to easily collect all communications and documents to present to legal authorities, expediting the resolution process. The platform is implemented using the Internet Computer Protocol (ICP) for secure, on-chain storage and application hosting, and is integrated with the Ethereum blockchain to leverage its extensive decentralized finance (DeFi) ecosystem, significant liquidity, and robust stablecoin infrastructure, thereby facilitating secure financial transactions. Moreover, we introduce an SSI-based authentication and authorization framework that spans across the entire platform, including both the Ethereum Virtual Machine (EVM) and Internet Computer Protocol (ICP), enabling unified role-based access control through verifiable credentials. A value-added of the present Communication, the framework is demonstrated by means of a detailed case study in the coffee industry, highlighting the technical challenges addressed during implementation. While quantitative efficiency metrics will be established through upcoming real-world testing with industry partners, the platform’s design aims to streamline operations by reducing intermediary dependencies and automating key processes. Finally, the Communication provides insights into its adaptability to other industries facing comparable supply chain challenges, presenting an approach focused on enhancing trust and reducing reliance on intermediaries. Full article

Physical Trading Card Games (TCGs) face inherent challenges, including vulnerability to theft, damage, and counterfeiting. Trading systems primarily depend on third-party marketplaces that collect fees from each trade, without benefiting the game developers. Players also deal with problems associated with shipping, such as high prices, long shipping times, and the risk of counterfeit goods. This paper introduces a blockchain-based solution that decouples card ownership from the physical media, which represents ownership with secure and verifiable digital tokens. The system leverages Ethereum Virtual Machine (EVM), the ERC-1155 standard, and InterPlanetary File System (IPFS) storage, ensuring flexibility, scalability, and cost-efficiency. The adoption of the lazy minting technique minimizes upfront costs for game developers by creating tokens only when acquired by end users. Physical representations of such digital goods can be printed on demand as they remain only a game accessory. The system also provides low-cost exchanges, significantly reducing the financial and logistical burdens associated with the trading of physical assets. Finally, the protocol empowers developers to monetize secondary markets through transaction fees. This approach addresses the limitations of physical card systems and also unlocks new opportunities for innovation and revenue in the TCG ecosystem. Full article

This paper examines the impact of stringent regulations on personal data protection on customer perception of data security and online shopping behavior. In the context of the rapidly expanding e-commerce landscape, ensuring the security of personal data is a complex and crucial task. The study of several legal frameworks, including Malaysia’s compliance with EU regulations and Indonesia’s Personal Data Protection Law, provides valuable insights into consumer data protection. The challenges of balancing data safeguarding and unrestricted movement and tackling misuse by external entities are significant and require careful consideration. This research elucidates the pivotal role of trust in e-commerce environments and the deployment of innovative e-commerce models designed to minimize personal data sharing. By integrating advanced privacy-enhancing technologies and adhering to stringent regulatory standards such as the GDPR, this study demonstrates effective strategies for robust data protection. The paper contributes to the academic discourse by providing a comprehensive framework that synergizes legal, technological, and procedural elements to fortify data security and enhance consumer trust in digital marketplaces. This approach aligns with international data protection standards and offers a pragmatic blueprint for achieving sustainable data security in e-commerce. Full article

Our paper was inspired by the recent Society 5.0 initiative of the Japanese Government which seeks to create a sustainable human-centric society by putting to work recent advances in technology. One of the key challenges in implementing Society 5.0 is providing trusted and secure services for everyone to use. Motivated by this challenge, this paper makes three contributions that we summarize as follows: Our first main contribution is to propose a novel blockchain and smart contract-based trust and reputation service design to reduce the uncertainty associated with buyer feedback in marketplaces that we expect to see in Society 5.0. Our second contribution is to extend Laplace’s Law of Succession in a way that provides a trust measure in a seller’s future performance in terms of their past reputation scores. Our third main contribution is to illustrate three applications of the proposed trust and reputation service. Here, we begin by discussing an application to a multi-segment marketplace, where a malicious seller may establish a stellar reputation by selling cheap items, only to use their excellent reputation score to defraud buyers in a different market segment. Next, we demonstrate how our trust and reputation service works in the context of sellers with time-varying performance due, say, to overcoming an initial learning curve. We provide a discounting scheme where older reputation scores are given less weight than more recent ones. Finally, we show how to predict trust and reputation far in the future, based on incomplete information. Extensive simulations have confirmed the accuracy of our analytical predictions. Full article

The aim of this research has been to enable the management of trustworthy relationships between stakeholders, service providers, and physical assets, which are required in critical energy and mobility cyber–physical systems (CPS) applications. The achieved novel contribution is the concept of trustworthy communities with respective experimental solutions, which are developed by relying on verifiable credentials, smart contracts, trust over IP, and an Ethereum-based distributed ledger. The provided trustworthy community solutions are validated by executing them in two practical use cases, which are called energy flexibility and hunting safety. The energy flexibility case validation considered the execution of the solutions with one simulated and two real buildings with the energy flexibility aggregation platform, which was able to trade the flexibilities in an energy flexibility marketplace. The provided solutions were executed with a hunting safety smartphone application for a hunter and the smartwatch of a person moving around in the forest. The evaluations indicate that conceptual solutions for trustworthy communities fulfill the purpose and contribute toward making energy flexibility trading and hunting safety possible and trustworthy enough for participants. A trustworthy community solution is required to make value sharing and usage of critical energy resources and their flexibilities feasible and secure enough for their owners as part of the energy flexibility community. Sharing the presence and location in mobile conditions requires a trustworthy community solution because of security and privacy reasons, but it can also save lives in real-life elk hunting cases. During the evaluations, the need for further studies related to performance, scalability, community applications, verifiable credentials with wallets, sharing of values and incentives, authorized trust networks, dynamic trust situations, time-sensitive behavior, autonomous operations with smart contracts through security assessment, and applicability have been detected. Full article

In contemporary data-driven economies, data has become a valuable digital asset that is eligible for trading and monetization. Peer-to-peer (P2P) marketplaces play a crucial role in establishing direct connections between data providers and consumers. However, traditional data marketplaces exhibit inadequacies. Functioning as centralized platforms, they suffer from issues such as insufficient trust, transparency, fairness, accountability, and security. Moreover, users lack consent and ownership control over their data. To address these issues, we propose DataMesh+, an innovative blockchain-powered, decentralized P2P data exchange model for self-sovereign data marketplaces. This user-centric decentralized approach leverages blockchain-based smart contracts to enable fair, transparent, reliable, and secure data trading marketplaces, empowering users to retain full sovereignty and control over their data. In this article, we describe the design and implementation of our approach, which was developed to demonstrate its feasibility. We evaluated the model’s acceptability and reliability through experimental testing and validation. Furthermore, we assessed the security and performance in terms of smart contract deployment and transaction execution costs, as well as the blockchain and storage network performance. Full article

Since the COVID-19 pandemic has forced most industries to embrace an online platform utilizing technological breakthroughs, it has significantly impacted our daily lives. Businesses that use marketplaces to sell and trade products to customers while increasing their participation through online shopping or e-commerce are among the sectors that take advantage of these situations. The current study set out to evaluate the level of customer satisfaction, trust, and service quality of the e-commerce application to enhance the system and provide a better shopping experience. Facebook, Shopee, Lazada, Shein, and TikTok were the five e-commerce platforms evaluated. The Philippines was the location of this study, and at least 200 people answered the survey, which was conducted in-person and online and consisted of 72 questionnaires. The researchers assessed twelve latent variables: perceived security, customer satisfaction, application interface, brand equity, tangibility, reliability, responsiveness, assurance, empathy, and information credibility. Structural equation modeling and multi-criteria decision analysis were used to analyze the data. The findings demonstrated that assurance, application interface, information credibility, and brand equity directly impacted service quality. Moreover, a direct and significant correlation exists between customer satisfaction and service quality. Customers’ trust is significantly impacted by their level of satisfaction and perception of security. The e-commerce apps were ranked using a multi-criteria decision analysis technique, which is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on tangibility, responsiveness, assurance, reliability, and empathy. Facebook received a low rating, whereas Shopee was ranked highest. To further enhance the services offered, the lowest rated application may use the results from the combination of the TOPSIS and SEM results. Additionally, application providers, managers, and researchers examining the user–software interaction of relevant e-commerce applications might utilize the study’s results to enhance their services regarding the purchasing experience and provide a sustainable service. Finally, this study is among the first to use the structural modeling approach to evaluate customer trust and satisfaction while integrating service quality and TOPSIS. Full article