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Core enterprises are entering into close collaborations with multi-level manufacturing service providers to create and share value. However, credible data sharing in collaborative manufacturing supply chains is rare, which can lead to uncontrollable production distortions and delayed operational adjustments. Driven by blockchain technology, this study proposes a systematic framework for credible manufacturing data sharing for a cross-enterprise collaborative manufacturing supply chain (CMSC). To develop the needed method, a blockchain network system with blockchain nodes, distributed ledger, and Raft-based distributed node ordering service system was first modelled. Then, two automatic data upload algorithms were studied to ensure the reliability of off-chain manufacturing data sources from core enterprises, suppliers, and customers. Then, two types of smart contracts were designed to ensure the standardisation and co-validation of manufacturing data storage and query processes in the blockchain network. A demonstrative case was studied to validate the proposed blockchain-based credible manufacturing data sharing method. The results show that our work is effective for credible data sharing in CMSC, which makes it easier for core enterprises to better operate the CMSC and further stimulate enterprises to create a credible social community. [ABSTRACT FROM AUTHOR]

The proliferation of Internet of Things (IoT) devices generates vast amounts of data, traditionally stored, processed, and analyzed using centralized systems, making them susceptible to attacks. Blockchain offers a solution by storing and securing IoT data in a distributed manner. However, the low performance and poor scalability of blockchain technology pose significant challenges for its application in IoT networks. The primary obstacle is the distributed consensus protocol, while ensuring data transparency, integrity, and immutability in a decentralized and untrusted circumstances which often compromises scalability. To address this issue, this paper introduces the use of the Delegated Proof of Stake (DPoS) consensus algorithm and sharding techniques to enhance scalability in blockchain-based IoT networks. Experimental results indicate that system throughput increases synchronously with the test load. Our findings reveal a tradeoff between throughput, latency, and up-downstream time on the Inter Planetary File System (IPFS). Given the critical importance of latency and throughput in IoT networks, the results demonstrate that DPoS offers high throughput, parallel processing, and robust security while efficiently scaling the network. Furthermore, at a test load of 500 Transactions Per Second (TPS), the system achieves a maximum throughput of approximately 11.094 ms. However, when the test load exceeds 2000 TPS, the total processing time for transactions extends to 11.205 ms. This method is particularly suitable for constrained IoT networks. Compared to previous edge computing-based approaches, our scheme demonstrates superior throughput performance. [ABSTRACT FROM AUTHOR]

With the digital transformation of the construction industry, the need to improve construction business process collaboration and automation is increasing. However, as construction projects usually involve many stakeholders with complex relationships and insufficient mutual trust, the existing technologies cannot fulfill the requirements of the construction industry. This paper explores the integration of blockchain, smart contracts, and process automation technologies into construction business processes, shedding light on both managerial and technical challenges. The study introduces a comprehensive technical framework meticulously designed to align with the intricate nature of construction practices while focusing on the resolution of legal complexities associated with smart contract applications and the facilitation of process collaboration and automation. The framework comprises three core modules: (1) action definition and extension to process models, (2) standardized mapping for automatic smart contract generation, and (3) smart contract visualization for reliable process collaboration and automation. This multifaceted approach caters to the specific needs of construction management, standardization, interoperability, and visualization. The framework's practicality is further evaluated through real-world testing within a construction payment case, effectively showcasing its efficacy and applicability in tangible business scenarios. While this paper represents a significant step forward in addressing construction business process collaboration and automation challenges, it acknowledges the necessity for ongoing research and development to refine and expand these innovative solutions to meet the evolving demands of construction management. Practical Applications: Currently, there is a significant escalation in the severity of disputes within the construction industry. The adoption of blockchain technology allows for the redistribution of trust within a construction project, shifting reliance from individuals to the system itself for better collaboration and fewer disputes. Although blockchain can help foster a more secure and transparent environment, at the process level, an efficient workflow engine is needed to activate processes in this environment. Therefore, this study proposed an approach to generating smart contract codes based on construction business processes in a standardized way and further visually executing these codes for the processes with historical transactions stored in blockchain. This approach can reduce the effort of smart contract programming and improve the standardization and credibility of smart contract generation. It can also streamline the procedure from construction business process design to final execution via predefined and visual modules. Meanwhile, the generation prototype is open sourced to provide transparency and further enhance the approach. To indicate practical implications in the real world, this study provided a case of construction payment, but the solution is not limited to the payment scenario. [ABSTRACT FROM AUTHOR]

With the rapid development of the logistics industry and the continuous growth of e-commerce, effectively monitoring logistics warehouses has become increasingly important to ensure the security of goods and oversee activities within storage facilities. Although current surveillance systems provide a certain level of security for logistics warehouses, they still face issues such as data tampering, storage, and access management. These challenges can compromise the integrity of surveillance video data, making the system vulnerable to unauthorized access. To address these challenges, this paper proposes the implementation of blockchain-based security management and access control of video data in logistics warehouses. Specifically, the solution employs the Hyperledger Fabric consortium blockchain to execute smart contracts and store the hash values of video data, thereby detecting any tampering and enhancing the security and integrity of the data. Additionally, hybrid encryption technology is utilized to ensure the confidentiality of video data during transmission and storage. Furthermore, the solution leverages the InterPlanetary File System (IPFS) for distributed video storage. This not only increases the redundancy and accessibility of data storage but also reduces the risk of single-point failures. A Role-Based Access Control (RBAC) mechanism is also introduced to strictly manage access permissions to video data, ensuring that only authorized users can access the data, thereby effectively preventing unauthorized access and data breaches. Through a comprehensive analysis of computational and communication costs and the evaluation of blockchain performance at 100 transactions per second for different transaction volumes using Hyperledger Caliper, the results demonstrate the effectiveness and efficiency of the proposed method. Compared to current research, this solution exhibits higher security, providing a new approach for the secure management and access control of video data in logistics warehouses. [ABSTRACT FROM AUTHOR]

The application of healthcare systems has led to an explosive growth in personal electronic health records (EHRs). These EHRs are generated from different healthcare institutions and stored in cloud data centers, respectively. However, data owners lose the authority to control and track their private and sensitive EHRs. In fact, data owners cannot establish rules for EHRs exchanging and sharing, nor can they verify the integrity of EHRs stored in semi-trusted clouds. Hence, an individual-centric access control framework is required to realize data access control. In this study, we construct a data access control framework, which integrates decentralized smart contracts and role-based access control (RBAC) to provide fine-grained data access control services. The key ideas of this schme includes: (1) a fine-grained access control framework for EHRs is proposed to achieve trusted access control; (2) a personalized policies definition mechanism is adopted to achieve patient-centric data access control; (3) a integrity checking mechanism for the shared EHRs is implemented to ensure the availability of medical records. Finally, we analyze the security properties of this scheme and develop a prototype system to evaluate its performance. Both theoretical analysis and experiment results demonstrate that this scheme can provide fine-grained access control and efficient integrity checking services for EHRs. [ABSTRACT FROM AUTHOR]

In the backdrop of the escalating incidents of mobile device theft and associated security challenges, a resilient and innovative solution is imperative. The traditional security mechanisms, largely reliant on the International Mobile Equipment Identity (IMEI), have been fraught with vulnerabilities, leading to a surge in incidents of device theft and data breaches. Addressing this pressing issue, we present a novel, two-tiered approach integrating sensor technology and blockchain to bolster mobile device security. This work aims to create and assess a dual-layered security strategy that uses blockchain and sensor technologies in a complementary way. Based on a rigorous conceptual framework, it explores a two-tiered security model that intricately combines sensor and blockchain technologies. This collaborative integration aims to provide an effective solution to the widespread challenges of theft and security breaches in mobile devices. The methodology employs a sensor layer for real-time data collection and processing to detect potential thefts, and activating alerts. The blockchain layer, invoked upon these alerts, initiates secure, transparent, and decentralized transactions for verification and validation across network nodes. This dual mechanism ensures swift and secure anti-theft actions, supported by an enhanced encryption standard. Our result analysis reveals the proposed system's superiority in computational time, energy consumption, and overall security levels when compared to existing protocols. The integration of real-time processing and blockchain's immutable nature promises reduced false positives and enhanced data integrity. The findings indicate that this integrative approach not only mitigates theft but also ensures data security, marking a significant stride in mobile security technology. In conclusion, this two-layered system promises a scalable, efficient, and robust solution to mobile device theft and data breaches, with potential impacts transcending individual device security to influence broader data privacy and security paradigms, thus signifying a pivotal development in the field of mobile security. [ABSTRACT FROM AUTHOR]

Sustainable professional integrity is the pivoting factor for maintaining the expected ethical standard of a profession. Whereas privacy of a user becomes vulnerable due to the digital transactions performed on the web. To this end, we propose a distributed framework, Jurisprudence, that preserves a user's privacy by preventing concurrent active sessions. The proposed model enables online transactions using one-time password (BLOCK-OTP) based blockchain multi-factor authentication. It encapsulates the users details and preserves the privacy of the user by preventing the invocation of concurrent transaction sessions. We deployed the system into the Ethereum test blockchain environment and tested the framework. We envisage our model to be suitable for the detection of fraudulent and malicious activities in near future. [ABSTRACT FROM AUTHOR]

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs. [ABSTRACT FROM AUTHOR]

The transportation industry has been recognized as one of the industries that can benefit from investment in blockchain-based systems and services that enable distributed data management and improve the effectiveness and efficiency of the transportation sector. However, the literature needs a guiding framework for integrating blockchain in issuing and preserving public transportation transactions in a technical environment that is secure, efficient, and transparent. This study proposes a blockchain-based transportation wallet (BTW) framework that facilitates the main digital transactions across diverse public transportation services. BTW embodies leveraging blockchain technology, which provides a decentralized and immutable ledger that records and verifies transactions, ensuring trust and reducing the risk of fraud. The framework has been validated by developing a blockchain-based public transportation smart wallet named "RideChain". This serves as a single decentralized point for making public transportation transactions and payments, as well as identity authorizations and management. RideChain enhances passengers' and service providers' experience through a secure and authentic platform for offering several reliable public transportation transactions efficiently. In this study, we implemented a smart contract to establish a protocol between passengers and journey services. The testing methodologies used in this study comprise unit testing, integration testing, performance testing, and user acceptance testing. The findings suggest that BTW has been successfully verified to demonstrate its capability for secure transactions, authenticity of monetary transactions, automated smart contracts, decentralized identity authentication, and effortless payments. [ABSTRACT FROM AUTHOR]

Blockchain technology has gained significant attention and widespread adoption due to several key factors, such as immutability, higher security, decentralization, transparency, smart contracts and automation, efficiency and cost savings, and the potential for innovation in numerous industries, including finance, healthcare, supply chain, real estate, education sector, and many more. Nowadays, the forgery of educational certificates is a concerning issue that poses significant challenges to academic institutions, employers, and individuals seeking authentic qualifications. Here, we propose a secure and notarized educational certificate authentication and verification framework named EduCert-Chain using Hyperledger Fabric to overcome concerns. EduCert-Chain uses ECDSA (Elliptic Curve Digital Signature Algorithm) for digital signature and verification, the SHA-256 algorithm for cryptographic hashing, and the raft consensus mechanism for validating network transactions. We have used the Hyperledger Caliper tool to conduct an extensive set of experiments to evaluate the performance of the proposed framework in terms of throughput and latency. We have considered two HEIs (Higher Education Institutions) organizations for the experimental evaluations, and the transaction ranges between 50–500. We have used CouchDB as a state database and the Docker container to handle highly portable workloads. Our framework achieves an average throughput for the query function, which is 34.95 TPS, and for the open function, it is 32.23 TPS. Additionally, it achieves an average latency of 4.21 s for the query function and 2.05 s for the open function. We also have conducted a comparative analysis to assess security features and limitations between the proposed framework and related work. Our observation reveals that the proposed EduCert-Chain framework has better features. This initiative will positively contribute towards addressing the issues of fraudulent credentials and forgery. [ABSTRACT FROM AUTHOR]

Fake products have become a major concern for businesses and consumers alike, resulting in significant economic losses and potential risks to consumers. Traditional methods of product authentication often fall short in the face of sophisticated counterfeit operations. Blockchain technology, with its decentralized and immutable nature, offers a promising solution to tackle this issue. This article provides a comprehensive overview of the use of blockchain for fake product identification. It begins by discussing the prevalence and impact of counterfeit products on various industries, highlighting the urgent need for an effective anti-counterfeiting system. The paper uses the fundamentals of blockchain technology, explaining its core concepts and features that make it suitable for this application. Next, the paper explores the key components of a blockchain-based system for fake product identification, including product registration, supply chain tracking, and consumer verification. It examines how blockchain can provide a tamper-proof and transparent ledger for recording and verifying product information at each stage of the supply chain. Additionally, the paper analyzes various consensus mechanisms and smart contract functionalities that enhance the security and efficiency of the system. The article also addresses the challenges and limitations associated with implementing blockchain-based anti-counterfeiting solutions, such as scalability, interoperability, and user adoption. It discusses potential strategies and emerging technologies that can mitigate these challenges and drive widespread adoption of blockchain for product authentication. [ABSTRACT FROM AUTHOR]

Modern advances in technology have increased the demand for traditional accounting systems to be upgraded for real-time data processing, security, and standardized reports. Thus, this paper proposes a new accounting information system that integrates IoT, blockchain, and XBRL. The proposed system aims to automate the accounting process by using IoT to collect data and send it automatically to a blockchain, which acts as a database that will generate journal entries automatically through smart contracts. XBRL will then be used as an output method for standardized financial reports based on the data transferred from the blockchain. This paper uses a qualitative research design based on semi-structured interviews with 13 industry experts from IT engineering, academia, and financial systems analysis. NVivo software was used to conduct a thematic analysis of interview transcripts. The findings demonstrated that integrating IoT, blockchain, and XBRL is technically feasible, with significant potential to enhance accounting systems. Additionally, the findings identified key challenges of the proposed system, including the complexity of integration, data validation across technologies, costs, user adoption, and scalability concerns. However, the results showed that this system offers substantial benefits, such as real-time data capture from IoT devices, secure data storage and immutability through blockchain, standardized financial reporting via XBRL, accounting process automation, improved data accuracy, and enhanced security and transparency in financial reporting. The study also identified an optimal mechanism for ensuring seamless data transmission between these technologies. The study makes a valuable contribution to the accounting field by providing a new framework for automating data collection, enhancing data security, and streamlining financial reporting, with significant potential to advance accounting systems and improve transparency, accuracy, and efficiency in financial reporting. The study's potential to impact accounting systems and financial reporting research and practice emphasizes its importance. [ABSTRACT FROM AUTHOR]

NFTs (non-fungible tokens) enable the commercialization of goods and services through blockchain technology, enhancing the security, transparency, and speed of transactions. The primary challenge NFTs face is their connection to the underlying asset, ensuring that transferring the token also means transferring the linked asset. This interdisciplinary article examines the technical and legal challenges of creating and linking a digital asset to an NFT. To explain the binding process, an NFT associated with a digital artwork was created, and relevant internal and uniform legal regulations were analyzed. [ABSTRACT FROM AUTHOR]

The substantial value held by smart contracts (SCs) makes them an enticing target for malicious attacks. The process of fixing vulnerabilities in SCs is intricate, primarily due to the immutability of blockchain technology. This research paper introduces a systematic literature review (SLR) that evaluates rectification systems designed to patch vulnerabilities in SCs. Following the guidelines set forth by the PRISMA statement, this SLR meticulously reviews a total of 31 papers. In this context, we classify recently published SC automated repair frameworks based on their methodologies for automatic program repair (APR), rewriting strategies, and tools for vulnerability detection. We argue that automated patching enhances the reliability and adoption of SCs, thereby allowing developers to promptly address identified vulnerabilities. Furthermore, existing automated repair tools are capable of addressing only a restricted range of vulnerabilities, and in some cases, patches may not be effective in preventing the targeted vulnerabilities. Another key point that should be taken into account is the simplicity of the patch and the gas consumption of the modified program. Alternatively, large language models (LLMs) have opened new avenues for automatic patch generation, and their performance can be improved by innovative methodologies. [ABSTRACT FROM AUTHOR]

Healthcare Information Exchange (HIE) is becoming a fundamental operation in current healthcare systems. In such systems, electronic health records (EHRs) are digitally stored inside each medical centers and, sometimes, are required to be shared between various healthcare facilities (HCFs). Indeed, sharing patient information is crucial and might be vulnerable to power outages, data misuse, privacy or security violations, and an audit trail. Hence, researchers have focused recently on cutting-edge technologies to develop secure HIE systems and ensure data privacy during transactions. Among such technologies, blockchain and artificial intelligence (AI) occupy a vital role in researchers' focuses and efforts to detect risky transactions in HIE systems, thus enhancing their security and privacy. While the blockchain allows HCFs to link to each other without requiring a central authority, AI models offer an additional security layer when sharing patient data between HCFs. This paper presents a survey about HIE systems, and the aim is two-fold: we first present the architecture of HIE systems along with their challenges; then, we categorize and classify the current state-the-art-techniques that show the potential of using blockchain and AI technologies in such systems. [ABSTRACT FROM AUTHOR]

Background: Blockchain technology provides a secure and decentralized platform for storing and transferring sensitive medical data, which can be utilized to enable remote medical consultations. Aim: A theoretical framework for creating a blockchain-based digital system created to facilitate telemedicine system. Results: This paper proposes a theoretical framework based on Hyperledger fabric for creating a blockchain-based digital entity to facilitate telemedicine services. The proposed framework utilizes blockchain technology to provide a secure and reliable platform for medical practitioners to interact remotely with patient transactions. Conclusion: The blockchain will serve as a one-stop digital service to secure patient data, ensure privacy, and facilitate payments. The proposed framework leverages the existing Hyperledger fabric platform to build a secure blockchain-assisted telemedicine platform. [ABSTRACT FROM AUTHOR]

Blockchain is an emerging technology with the potential to radically transform logistics in the highly complex environment of the agri-food supply chain. The key challenges of the agri-food sector include overcoming the limitations (time, cost and quality) to developing global and efficient transparency and traceability of food, eliminating expensive intermediaries, and ensuring no disruption between suppliers and retailers. This paper describes a practical approach by not only using smart contracts to integrate various stakeholders but also incorporating a Public Participation Geographic Information System platform to ensure traceability of the operations conducted in an agri-food supply chain. As a factor in improving distribution and minimising intermediaries, third-party logistics participation is included in this research. Through a case study, the entities and interactions between processes within a blockchain system based on a smart contract are identified. The findings reveal an innovative blockchain approach to logistics in the agri-food supply chain. [ABSTRACT FROM AUTHOR]

This study presents an innovative approach using the Ethereum blockchain to democratize access to tutoring services, advancing educational technology by bridging the affordability gap for learners with limited financial resources. This solution enables low-income learners to access tutoring services without significant expenses by eliminating intermediaries through smart contracts. Learners can directly book tutoring services based on fees and evaluations, ensuring a fair and accessible experience. The findings show that this approach reduces tutoring expenses and improves trust and accountability through transparent transactions and feedback mechanisms. The proposed system demonstrates how blockchain technology can foster a more equitable and efficient educational landscape, offering personalized support to all learners regardless of their economic background. [ABSTRACT FROM AUTHOR]

IT has made significant progress in various fields over the past few years, with many industries transitioning from paper-based to electronic media. However, sharing electronic medical records remains a long-term challenge, particularly when patients are in emergency situations, making it difficult to access and control their medical information. Previous studies have proposed permissioned blockchains with limited participants or mechanisms that allow emergency medical information sharing to pre-designated participants. However, permissioned blockchains require prior participation by medical institutions, and limiting sharing entities restricts the number of potential partners. This means that sharing medical information with local emergency doctors becomes impossible if a patient is unconscious and far away from home, such as when traveling abroad. To tackle this challenge, we propose an emergency access control system for a global electronic medical information system that can be shared using a public blockchain, allowing anyone to participate. Our proposed system assumes that the patient wears a pendant with tamper-proof and biometric authentication capabilities. In the event of unconsciousness, emergency doctors can perform biometrics on behalf of the patient, allowing the family doctor to share health records with the emergency doctor through a secure channel that uses the Diffie-Hellman (DH) key exchange protocol. The pendant's biometric authentication function prevents unauthorized use if it is stolen, and we have tested the blockchain's fee for using the public blockchain, demonstrating that the proposed system is practical. [ABSTRACT FROM AUTHOR]

Security is an important consideration when delivering information-aware messages to vehicles that are far away from the current location of the information-sending vehicle. This information helps the receiver to save fuel and time by making wise decisions to avoid damaged or blocked roads. To ensure the safety and security of this type of information using blockchain technology, we propose a new cognitive vehicular communication scheme to transfer messages from source to destination. Due to spectrum scarcity in vehicular networks, there needs to be a wireless medium available for every communication link since vehicles require it to communicate. The primary user (PU) makes a public announcement about a free channel to all secondary users nearby and only gives it to authentic vehicles. The authenticity of vehicles is guaranteed by a roadside unit (RSU) that offers secure keys to any vehicle that joins this blockchain network. Those who participate in this network must pay a certain amount and receive rewards for their honesty that exceed the amount spent. To test the performance of various parameters, the proposed scheme utilizes the Ethereum smart contract and compares them to blockchain and non-blockchain methods. Our results show a minimum delivery time of 0.16 s and a minimum overhead of 350 bytes in such a dynamic vehicle environment. [ABSTRACT FROM AUTHOR]

In recent years, rapid technological advancements have propelled blockchain and artificial intelligence (AI) into prominent roles within the digital industry, each having unique applications. Blockchain, recognized for its secure and transparent data storage, and AI, a powerful tool for data analysis and decision making, exhibit common features that render them complementary. At the same time, machine learning has become a robust and influential technology, adopted by many companies to address non-trivial technical problems. This adoption is fueled by the vast amounts of data generated and utilized in daily operations. An intriguing intersection of blockchain and AI occurs in the realm of federated learning, a distributed approach allowing multiple parties to collaboratively train a shared model without centralizing data. This paper presents a decentralized platform FBLearn for the implementation of federated learning in blockchain, which enables us to harness the benefits of federated learning without the necessity of exchanging sensitive customer or product data, thereby fostering trustless collaboration. As the decentralized blockchain network is introduced in the distributed model training to replace the centralized server, global model aggregation approaches have to be utilized. This paper investigates several techniques for model aggregation based on the local model average and ensemble using either local or globally distributed validation data for model evaluation. The suggested aggregation approaches are experimentally evaluated based on two use cases of the FBLearn platform: credit risk scoring using a random forest classifier and credit card fraud detection using a logistic regression. The experimental results confirm that the suggested adaptive weight calculation and ensemble techniques based on the quality of local training data enhance the robustness of the global model. The performance evaluation metrics and ROC curves prove that the aggregation strategies successfully isolate the influence of the low-quality models on the final model. The proposed system's ability to outperform models created with separate datasets underscores its potential to enhance collaborative efforts and to improve the accuracy of the final global model compared to each of the local models. Integrating blockchain and federated learning presents a forward-looking approach to data collaboration while addressing privacy concerns. [ABSTRACT FROM AUTHOR]

Exploring the data quality problems in the context of federated cooperation and adopting corresponding governance countermeasures can facilitate the smooth progress of federated cooperation and obtain high-performance models. However, previous studies have rarely focused on quality issues in federated cooperation. To this end, this paper analyzes the quality problems in the federated cooperation scenario and innovatively proposes a "Two-stage" data quality governance framework for the federated collaboration scenarios. The first stage is mainly local data quality assessment and optimization, and the evaluation is performed by constructing a metrics scoring formula, and corresponding optimization measures are taken at the same time. In the second stage, the outlier processing mechanism is introduced, and the Data Quality Federated Averaging (Abbreviation DQ-FedAvg) aggregation method for model quality problems is proposed, so as to train high-quality global models and their own excellent local models. Finally, experiments are conducted in real datasets to compare the model performance changes before and after quality governance, and to validate the advantages of the data quality governance framework in a federated learning scenario, so that it can be widely applied to various domains. The governance framework is used to check and govern the quality problems in the federated learning process, and the accuracy of the model is improved. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are promising tools in mobile communication due to their flexibility. However, the rapid development of mobile communications further intensifies the challenge of spectrum scarcity, necessitating spectrum sharing with other systems. We suggest a Spectrum Sharing Algorithm for a UAV-Assisted Relay System. The utility function of secondary users (SUs) is defined by their communication rate, rewards from relay primary users (PUs), and spectrum leasing expenses. The utility function of PUs consists of their communication rate and revenue from spectrum leasing. We propose a joint optimization algorithm for the positioning and power allocation of UAVs, maximizing the frequency spectrum utilization rate of users. Spectrum trading between PUs and SUs is modeled as a Stackelberg game, and the problem is solved by using Lagrange multipliers and KKT conditions. To enhance the security of spectrum trading, a reputation-based spectrum sharing blockchain consensus algorithm is designed. We utilize Shamir's secret sharing method to reduce computational complexity. Additionally, we design a smart contract to optimize the functionality of transaction transfers. The findings demonstrate that the proposed algorithm enhances the benefits for both participants in spectrum sharing, while safeguarding the security of spectrum transactions. [ABSTRACT FROM AUTHOR]

Summary The proliferation of network devices capable of gathering, transmitting, and receiving data over the Internet has spurred the widespread adoption of Internet of Things (IoT) devices, particularly in resource‐oriented applications. Integrating blockchain, IoT, homomorphic encryption, and federated learning requires a balance between computational requirements and real‐time performance. Secure key management is crucial to maintain data privacy and integrity. Compliance with privacy regulations requires careful implementation of privacy‐preserving mechanisms in blockchain‐enabled IoT environments, which can be subjected to various attacks. Addressing these challenges requires interdisciplinary expertise, research, and innovation to develop more efficient and effective privacy‐preserving techniques tailored to the unique characteristics of such environments. This research introduces the Modified Homomorphic Encryption Federated‐based Adaptive Hybrid Dandelion Search (MHEF‐AHDS) algorithm as an effective framework to enhance security in blockchain‐enabled IoT systems. The amalgamation of Modified Homomorphic Encryption (MHE) and Federated Learning (FL) constitutes a potent alliance that addresses privacy concerns within collaborative and decentralized machine learning environments. This facilitates secure and adaptable data collaboration, effectively mitigating privacy risks associated with sensitive information. The integration of quantum machine learning into security applications presents an exciting opportunity for distinctive progress and innovation. Within this work, the Adaptive Hybrid Dandelion optimization algorithm, featuring an Initial search strategy, is employed for hyperparameter optimization thereby elevating the performances of the proposed MHEF‐AHDS method. Furthermore, the integration of smart contracts and Blockchain‐based IoT enhances the overall security of the proposed method. MHEF‐AHDS comprehensively tackles privacy, security, and scalability challenges through robust security measures and privacy enhancements. The performance evaluation of the MHEF‐AHDS method encompasses a thorough analysis based on key metrics such as throughput, latency, scalability, energy consumption, accuracy, precision, recall, and f1‐score. Comparative assessments against existing methods are conducted to gauge the effectiveness of the proposed method in addressing security, privacy, and scalability concerns. [ABSTRACT FROM AUTHOR]

Modern healthcare systems have two main sections: electronic health records (EHRs) and remote patient monitoring (RPM). With these sections, several issues have arisen related to comprehensiveness, which these sections lack in covering all the data information about the patient’s state, and other issues in privacy and security. Many types of research have been presented to solve these issues or mitigate their effects. One of these ideas is to use blockchain technology. However, some research may not utilize this technique properly, where data comprehensiveness problems remain and the preservation of individual nodes' data may be compromised. This paper introduces a new system called Patient Health Record (PHR), which will provide comprehensive patient health data and IoT device reading. PHR data is protected using a multi-peer, distributed, and decentralized system based on blockchain. A smart contract has been created for the system through which the PHR data will be cached in the blockchain. It is deployed on the Proof of Authority network to increase the speed of transaction processing, which is important in processing data for IoT devices. The proposed system is evaluated according to a range of metrics (cost, immutability, data storage, and estimated time) to validate the system. [ABSTRACT FROM AUTHOR]

To solve the problems of severe centralization and vulnerability to data tampering in traditional seafood traceability systems, the blockchain technology was employed to design the seafood traceability system based on hazard analysis and critical control points (HACCP). The multiple linear regression was used to process the sample data indicators and confirm the critical control points in the farming process. Based on the determination of key information, the smart contracts were designed to verify the uploaded data at each stage of seafood traceability. From the perspective of system feasibility, the detailed designs were conducted for system functionality, consensus topology and traceability coding. The seafood traceability system was developed and subjected to function and performance testing. The results show that the system transaction throughput is consistently around 320 transactions per second. The average transaction latency is approximate 0.5 s, and the transaction success rate is about 99.8%. The performance is fully capable of meeting the needs of production practices. [ABSTRACT FROM AUTHOR]

In other instances, the cloud transfers payment information directly to the merchant's server without first doing any fraud checks. Block authentication between the cloud and a healthcare merchant server is the goal of this study, which is designed to prevent the deployment of fraudulent servers. Smart contract verification on the blockchain will be used to this end. The cloud assault must be prevented from accessing personal payment and card information. It is via the employment of cryptography methods that this concept of privacy reservation is made possible. The Boolean crossover depth first search (DFS) technique is used to encrypt data in the payment gateway protocol at its inception. When the hospital administrator solicits card data from patients or users, our innovative approach swiftly initiates data encryption using the DFS technique. This method meticulously traverses the data structure in a depth-first manner, employing Boolean operations to systematically encrypt sensitive information. Through this process, the patient's payment and card data undergo secure transformation, rendering it unreadable to unauthorized entities. Additionally, an authentication key is generated concurrently with the encryption process, enabling verification between the system and the user before any data transmission occurs. The integration of the DFS technique serves as a fundamental layer of defense against potential cloud-based attacks. Its application ensures the utmost protection of personal payment and card details throughout the transaction process, bolstering the security infrastructure of our proposed system. A comprehensive analysis comparing our approach with existing methods showcases the efficiency and reliability of our proposed system in terms of Execution Time (ms), Encryption Time (ms), Decryption Time (ms), and Memory (bits). This study aims to bridge the gap in transactional security, ensuring robust protection against unauthorized access and data breaches in healthcare payment transactions. [ABSTRACT FROM AUTHOR]

Smart contracts (SC) are programs embodying certain business logic stored on a blockchain network like Ethereum. The execution of transactions on SC has a cost, measured in gas units, that depends on the low‐level operations performed. Therefore, a poor choice of high‐level language constructs could lead to overcharging users for their transactions. Thus, a testing process focused on possible deviations of the gas used in diverse scenarios could provide substantial global savings. This paper presents a gas‐centered mutation testing approach for taking care of the gas consumed by Solidity SCs. This approach can be useful to improve the test quality to detect gas‐related problems, reason about performance issues that only manifest in certain situations, and identify alternative more optimal implementations. We define and implement several mutation operators specifically designed to perturb gas consumption while preserving contract semantics in general. Our experiments using several real‐world SCs show the feasibility of the technique, with some mutants reproducing meaningful differences in the consumption and exposing some gas limits not tight enough in historic transactions. Therefore, our approach is shown to be a good ally to prevent the appearance of gas‐related issues and lays the groundwork for researchers seeking to improve performance testing practices. [ABSTRACT FROM AUTHOR]

In this paper, we propose a smart contract-based multi-candidate self-tallying voting scheme in order to guarantee the privacy of ballots in the case of multiple candidates. This scheme uses the ElGamal cryptosystem to ensure the security of the ballots, and combines it with a Distributed Encryption algorithm to make the voting scheme have self-tallying features, and guarantees the correctness of the intermediate data through zero-knowledge proofs. The experimental results show that the scheme improves the voting efficiency without compromising the security. [ABSTRACT FROM AUTHOR]

In the era of cloud computing, guaranteeing the safety and effectiveness of data management is of utmost importance. This investigation presents a novel approach that amalgamates the sharding concept, encryption, zero-knowledge proofs (zkp), and blockchain technology for secure data retrieval and data access control to improve data security, efficiency in cloud storage and migration. Further, we utilize user-specific digital wallets for secure encryption keys in order to encrypt the file before storing into the cloud. As Large files (greater than 50 MB) or Big data files (greater than 1 TB) require greater computational complexity, we leverage the sharding concept to enhance both space and time complexity in cloud storage. Hence, the large files are divided into shards and stored in different database servers. We also employ a blockchain smart contract to enhance secure retrieval of the file and also a secure access method, which ensures the privacy of the user. The zk-snark protocol is utilized to ensure the safe transfer of data between different cloud services. By utilizing this approach, data privacy is preserved, as only the proof of the data's authenticity is shared with the verifier at the destination cloud, rather than the actual data themselves. The suggested method tackles important concerns related to data protection, privacy, and efficient resource utilization in cloud computing settings by ensuring it meets all the cloud policies required to store data. Since the environment maintains the privacy of the user data and the raw data of the user is not stored anywhere, the entire environment is set up as a Zero trust model. [ABSTRACT FROM AUTHOR]

With the rapid expansion of global trade, the complexity and diversification of supply chains have become increasingly significant. In particular, the supply chain for hazardous materials, involving chemicals and explosives, requires stringent regulation. Managing the flow of these high-risk goods necessitates a reliable access control system to ensure safety and compliance. Traditional supply chain management systems often rely on centralized databases and record-keeping systems, which are prone to tampering and single points of failure, making them inadequate for current high-security demands. This paper combines blockchain technology with a hazardous materials supply chain model. In the blockchain network, our innovation lies in the introduction of a transaction coordinator to create transaction sets for each supply chain entity along with smart contracts to implement access control for these transaction sets. We also propose a new hazardous materials supply chain model architecture and conduct experimental verification using simulated hazardous materials supply chain data. Our experimental results show that the proposed method performs excellently in throughput and latency tests, demonstrating the potential to enhance the efficiency and security of supply chain management. [ABSTRACT FROM AUTHOR]

As blockchain technology continues to mature, its potential for use in workflow systems has garnered considerable attention. However, the adoption of blockchain-based workflow systems in practical contexts presents a range of challenges that need to be addressed. Among the challenges encountered in the context of workflow systems, one particularly significant hurdle relates to establishing trust among the various actors participating in the workflow. To address this concern, we introduce a workflow architecture that incorporates provenance support and decentralized identifiers. This strategic combination aids in identifying what actions by whom led to the creation of the data being passed on within the workflow. The addition of provenance support within our framework results in a notable enhancement of traceability, accountability, and transparency throughout the workflow processes, which ultimately improves the overall trustworthiness of the system. The key novelty of this study can be found at the provenance-enabled blockchain workflow architecture that remains unexplored until now. The proposed solution is supported by a realistic use-case scenario portraying a used-car business which has undergone testing and measurements benchmarked against comparable frameworks and solutions. [ABSTRACT FROM AUTHOR]

Nowadays, healthcare takes a great attention from people and governments due to the emergence of new diseases and viruses. Health Information Exchange (HIE) allows doctors, clinicians, and healthcare facilities (HCF) to exchange and share patient records according to patient permission. Unfortunately, the HIE systems suffer from several challenges such as security, privacy, latency, throughput, and scalability. Thus, researchers proposed many techniques for efficient HIE, but they did not cover all challenges. This paper proposes an efficient architecture called ELSO that combines between public blockchain and off-chain in order to enhance the integrity and privacy of HIE systems. In this architecture, the patient information is divided into two categories: relative data containing personal information that will be stored in the public blockchain; sensitive data describing the patient situation that will be stored in the off-chain database. Furthermore, ELSO is composed of three layers: The first is called the application layer and aims to create patient profiles; the second layer is called the control layer and aims to control the specialist access, and the third layer is called the storage layer and allows to store data in blockchain and off-chain. To evaluate the performance of our framework, we used real healthcare data where the obtained results show the effectiveness of ELSO in terms of all metrics compared to other techniques. [ABSTRACT FROM AUTHOR]

We propose a novel blockchain-based academic degree verification system. The system relies on a smart contract deployed on the Ethereum blockchain platform. The system protects the privacy of the students who have been verified without the need of encryption, and hence, avoid the complexity of security key management and the potential disaster if the keys are stolen or revealed. The amount of degree data is also designed to be minimum for proper verification. All operations on the critical path of the system are automated without any human intervention. However, the system does assume that the organization would stand behind the proposed system to ensure the system's integrity. The system is open to anyone who wishes to verify the degree of a student. To prevent spamming and to support the long-term sustainability of the system, a small fee is charged for each verification request. A portion of the fees collected is immediately credited to the participating schools. To facilitate automated school enrollment into the system, any school may request to enroll by placing a significant amount of stake in ETH. The stake can be refunded when the school decides to leave the system. However, if the school is blacklisted due to misbehavior, the stake is confiscated. This design strongly discourages adversaries from abusing the system. The performance of the system is fully characterized with regard to the gas consumption of key operations in various use cases. We demonstrate that the system is conducive for long-term sustainability. [ABSTRACT FROM AUTHOR]

One of the most significant barriers to blockchain adoption is the need for a better user experience. Tasks such as account setup, key management, and transaction handling need to be streamlined to propel the next wave of technological adoption across various sectors. A promising solution to these issues lies in account abstraction, which aims to simplify the user experience by masking the underlying complexities of blockchain technology. The most notable effort to implement account abstraction is Ethereum's ERC-4337, a proposal that addresses these pain points by enhancing flexibility and ease of use for developers and end users alike. This paper explores the account abstraction architecture, its functions and how it can redefine blockchain utility, from smart contracts to smart reporting. [ABSTRACT FROM AUTHOR]

To address the limitations of current deep learning-based methods in extracting contract bytecode features and representing vulnerability semantics, as well as the shortcomings of the traditional graph neural networks in learning temporal information from contract statements, a method for detecting vulnerabilities in contracts was proposed based on pre-trained and temporal graph neural network. Firstly, the pre-trained model was used to transform smart contract bytecode into a vulnerability semantics-aware contract graph structure. Then, combined with a self-attention mechanism, the event-driven temporal graph neural network was designed to extract temporal information during contract execution. Finally, focusing on reentrant vulnerabilities, timestamp dependency vulnerabilities, and Tx. origin authentication vulnerabilities, extensive experiments were conducted on a dataset of 120 932 actual contracts. The results show that the proposed method significantly outperforms existing approaches. [ABSTRACT FROM AUTHOR]

The surging interest in digitalization has revitalized research for digital business model. Mobile Internet of Things (IoT) terminals will reach billions and become an important infrastructure for a digital and intelligent society. In the digital business model of IoT terminals, the electronic seal of commercial contracts are especially investigated to provide the same level security as guaranteed by the traditional seal. However, the existing electronic seal is only applicable to the centralized network applications, which severely relies on the certificate authority. In this paper, we propose a blockchain-based multi-signature smart contract electronic seal scheme. The key of our design is to deploy a smart contract for business parties on Ethereum for secure electronic seal towards mobile IoT terminals. Unlike the traditional seal, this electronic seal is verified and managed collectively by all mining nodes. Combining it with optimizations in terms of a multi-signature algorithm encoded in the smart contract, our design achieves complete digital contract functionality for all business participants of terminals. As an example, we demonstrate an implementation on the Goerli testnet of the Ethereum network with the smart contract deployment. The security analysis and evaluation demonstrate that our design is secure in its multi-signature implementation and can be used in practice. [ABSTRACT FROM AUTHOR]

With development of e-commerce and intelligent devices, large amounts of asset transaction data and traders' identity information have been generated. It poses huge challenges to the data security and privacy when data are stored in a centralized trading system. Here, considering the need of data sharing and data privacy in asset trading, we proposed a blockchain-based privacy protecting framework to accommodate both aspects of these requirements. The proposed framework combines a multi-channel access control model and smart contracts to enhance the security and transparency of asset trading within permissioned channels while maintaining privacy for transactions occurring outside of these channels. Furthermore, regarding market efficiency and transaction fairness, we design trading algorithm of double auction to make transaction more automated and intelligent. Finally, we implement asset trading prototype based on Hyperledger Fabric and evaluate the performance of model. The experimental results show that the proposed multi-channel blockchain-based framework realized intra-channel date sharing and extra-channel privacy protection. Our framework achieves enhanced security, high efficiency and strong traceability for assert trading. [ABSTRACT FROM AUTHOR]

Federated learning (FL) is a distributed machine learning approach that can enable Internet of Things (IoT) edge devices to collaboratively learn a machine learning model without explicitly sharing local data in order to achieve data clustering, prediction, and classification in networks. In previous works, some online multi-armed bandit (MAB)-based FL frameworks were proposed to enable dynamic client scheduling for improving the efficiency of FL in underwater wireless IoT networks. However, the security of online dynamic scheduling, which is especially essential for underwater wireless IoT, is increasingly being questioned. In this work, we study secure dynamic scheduling for FL frameworks that can protect against malicious clients in underwater FL-assisted wireless IoT networks. Specifically, in order to jointly optimize the communication efficiency and security of FL, we employ MAB-based methods and propose upper-confidence-bound-based smart contracts (UCB-SCs) and upper-confidence-bound-based smart contracts with a security prediction model (UCB-SCPs) to address the optimal scheduling scheme over time-varying underwater channels. Then, we give the upper bounds of the expected performance regret of the UCB-SC policy and the UCB-SCP policy; these upper bounds imply that the regret of the two proposed policies grows logarithmically over communication rounds under certain conditions. Our experiment shows that the proposed UCB-SC and UCB-SCP approaches significantly improve the efficiency and security of FL frameworks in underwater wireless IoT networks. [ABSTRACT FROM AUTHOR]

With the increasing popularity of Decentralized Applications (DApps) in blockchain, securing smart contracts has been a long-term, high-priority subject in the domain. Among the various research directions for vulnerability detection, fuzzing has received extensive attention because of its high effectiveness. However, with the increasing complexity of smart contracts, existing fuzzers may waste substantial time exploring locations irrelevant to smart contract vulnerabilities. In this article, we present FunFuzz, a function-oriented fuzzer, which is dedicatedly tailored for detecting smart contract vulnerability with high effectiveness and efficiency. The key observation in our research is that most smart contract vulnerabilities exist in specific functions rather than randomly distributed in all program code like other traditional software. To this end, unlike traditional fuzzers which mainly target code coverage, FunFuzz identifies risky functions while pruning non-risky ones in smart contracts. In this way, it significantly narrows down the exploration scope during the fuzzing process. In addition, FunFuzz employs three unique strategies to direct itself toward effectively discovering vulnerabilities specific to smart contracts (e.g., reentrancy, block dependency, and gasless send). Extensive experiments on 170 real-world contracts demonstrate that FunFuzz outperforms state-of-the-art fuzzers in terms of effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

Currently, the media industry is in the rapid development stage of media integration, which has brought about great changes in content production mode, presentation form, communication mechanism, operation and maintenance management, etc. At the same time, it is also faced with problems such as difficult information traceability, declining industry credibility, low data circulation quality and efficiency, difficult data security and user privacy protection, etc. Utilizing blockchain's characteristics can solve these problems that the media industry is currently facing. This paper designs a convergence media ecology model based on blockchain (CMEM-BC), focusing on the basic elements of the model, node operation and maintenance system, node management mechanism, value circulation mechanism, and storage mechanism, trying to establish a decentralized, traceable, and immutable convergence media ecosystem. On this basis, this paper summarizes the ecological framework and ecological model of CMEM-BC. Finally, the paper describes the verification of the effectiveness of CMEM-BC in key links through simulation experiments, verifying that CMEM-BC has high originality and is more suitable for the application of convergence media ecology through model analysis and comparison. [ABSTRACT FROM AUTHOR]

Blockchain (BCn) revolution across the world leads the global transformation by altering the existing structure and introducing the accessible and decentralized paradigm. This technology facilitates access to resources and redefines conventional frameworks, empowering people and communities globally. Motivated by these attention‐seeking potentiality of BCn features, in this article, we examine the challenges, advancements, and emerging prospects of the BCn revolution in Bangladesh. With a specific focus on BCn implications for sustainability and smart development, this study addresses the urgent need to understand how BCn can facilitate sustainable development in rapidly evolving countries like Bangladesh. The goal of this research is to draw attention to the successful revolution of BCn in the world and use this knowledge to extract best practices and cutting‐edge strategies for sustainable transformation of Bangladesh. The contribution of this study covers the underlying concepts of the BCn technology, showing the revolutionary state of BCn across the world, applications of BCn for sustainability, assessment of its current usage, and highlighting the BCn implementation problems. Furthermore, this study serves as a gateway to a transparent, decentralized future that fosters inclusive national progress and aligns with sustainable development goals. This study also strives to inspire individuals to use this transformational technology for the collective benefit of society by highlighting BCn's potential to empower communities while driving positive change. [ABSTRACT FROM AUTHOR]

In the era of big data in response to the conflict between the reliability enhancement of user data in cloud server storage and the strategy for removing duplicate data, a heterogeneous server data security deduplication method was proposed blockchain-based smart contracts. Leveraging the decentralized, tamper-proof, and publicly transparent characteristics of blockchain, as well as the automation capabilities of smart contracts, this method could achieve data storage security, reliability, and privacy protection. Specifically, the method combined secret sharing and blockchain smart contract technology to design a secure and efficient cloud storage data deduplication service. Moreover, by replacing the role of centralized third-party entities with blockchain and mitigating server heterogeneity through smart contract scripts, potential security risks were eliminated. Experimental results demonstrated that, under various scenarios with different file sizes and block quantities, the average computational overhead of this method was 65.42% to 115.77% lower than the comparative solutions, and the average storage overhead was 7.94% to 19.50% lower. Additionally, for varying numbers of heterogeneous storage servers, this method exhibited significantly lower average computational and storage overhead, with reductions of 67.27% to 177.89% and 34.01 % to 72.89%, respectively. Therefore, the proposed approach could outperform two existing blockchain-based deduplication method in terms of security, computational and storage efficiency. [ABSTRACT FROM AUTHOR]

The financial landscape is undergoing a revolution with the Decentralized Finance (DeFi), poised to reshape business value creation. This study provides an overview of research progress in DeFi from both business and information systems perspectives. Employing a hybrid bibliographic approach and TCM framework, we aim to uncover collaboration trends, developmental characteristics, and knowledge structures. Through various network analyses, including co-occurrence networks and keyword networks, as a multidisciplinary field with a focus on leveraging emerging, DeFi can construct decentralised ecosystems for finance. Looking ahead, there is potential to further explore the advantages of DeFi in maximising value creation. [ABSTRACT FROM AUTHOR]

Mobile edge computing (MEC) technology is widely used for real‐time and bandwidth‐intensive services, but its underlying heterogeneous architecture may lead to a variety of security and privacy issues. Blockchain provides novel solutions for data security and privacy protection in MEC. However, the scalability of traditional blockchain is difficult to meet the requirements of real‐time data processing, and the consensus mechanism is not suitable for resource‐constrained devices. Moreover, the access control of MEC data needs to be further improved. Given the above problems, a data privacy protection model based on sharding blockchain and access control is designed in this paper. First, a privacy‐preserving platform based on a sharding blockchain is designed. Reputation calculation and improved Proof‐of‐Work (PoW) consensus mechanism are proposed to accommodate resource‐constrained edge devices. The incentive mechanism with rewards and punishments is designed to constrain node behavior. A reward allocation algorithm is proposed to encourage nodes to actively contribute to obtaining more rewards. Second, an access control strategy using ciphertext policy attribute‐based encryption (CP‐ABE) and RSA is designed. A smart contract is deployed to implement the automatic access control function. The InterPlanetary File System is introduced to alleviate the blockchain storage burden. Finally, we analyze the security of the proposed privacy protection model and statistics of the GAS consumed by the access control policy. The experimental results show that the proposed data privacy protection model achieves fine‐grained control of access rights, and has higher throughput and security than traditional blockchain. [ABSTRACT FROM AUTHOR]

The imbalance between parking availability and demand has led to a rise in traffic challenges in many cities. The adoption of technologies like the Internet of Things and deep learning algorithms has been extensively explored to build automated smart parking systems in urban environments. Non-human-mediated, scalable smart parking systems that are built on decentralized blockchain systems will further enhance transparency and trust in this domain. The presented work, PARKTag, is an integration of a blockchain-based system and computer vision models to detect on-field free parking slots, efficiently navigate vehicles to those slots, and automate the computation of parking fees. This innovative approach aims to enhance the efficiency, scalability, and convenience of parking management by leveraging and integrating advanced technologies for real-time slot detection, navigation, and secure, transparent fee calculation with blockchain smart contracts. PARKTag was evaluated through implementation and emulation in selected areas of the MIT Art Design Technology University campus, with a customized built-in dataset of over 2000 images collected on-field in different conditions. The fine-tuned parking slot detection model leverages pre-trained algorithms and achieves significant performance metrics with a validation accuracy of 92.9% in free slot detection. With the Solidity smart contract deployed on the Ethereum test network, PARKTag achieved a significant throughput of 10 user requests per second in peak traffic hours. PARKTag is implemented as a mobile application and deployed in the mobile application store. Its beta version has undergone user validation for feedback and acceptance, marking a significant step toward the development of the final product. [ABSTRACT FROM AUTHOR]

Smart contracts are programs that reside and execute on a blockchain, like any transaction. They are automatically executed when preprogrammed terms and conditions are met. Although the smart contract (SC) must be presented in the blockchain for the integrity of data and transactions stored within it, it is highly exposed to several vulnerabilities attackers exploit to access the data. In this paper, classification and detection of vulnerabilities targeting smart contracts are performed using deep learning algorithms over two datasets containing 12,253 smart contracts. These contracts are converted into RGB and Grayscale images and then inserted into Residual Network (ResNet50), Visual Geometry Group-19 (VGG19), Dense Convolutional Network (DenseNet201), k-nearest Neighbors (KNN), and Random Forest (RF) algorithms for binary and multi-label classification. A comprehensive analysis is conducted to detect and classify vulnerabilities using different performance metrics. The performance of these algorithms was outstanding, accurately classifying vulnerabilities with high F1 scores and accuracy rates. For binary classification, RF emerged in RGB images as the best algorithm based on the highest F1 score of 86.66% and accuracy of 86.66%. Moving on to multi-label classification, VGG19 stood out in RGB images as the standout algorithm, achieving an impressive accuracy of 89.14% and an F1 score of 85.87%. To the best of our knowledge, and according to the available literature, this study is the first to investigate binary classification of vulnerabilities targeting Ethereum smart contracts, and the experimental results of the proposed methodology for multi-label vulnerability classification outperform existing literature. [ABSTRACT FROM AUTHOR]

The online services provided by the Service Provider (SP) have brought significant convenience to people's lives. Nowadays, people have grown accustomed to obtaining diverse services via the Internet. However, some SP utilize or even tamper with personal data without the awareness or authorization of the Data Provider (DP), a practice that seriously undermines the authenticity of the DP's authorization and the integrity of personal data. To address this issue, we propose a Verifiable Authorization Information Management Scheme (VAIMS). During the authorization process, the authorization information and personal data fingerprints will be uploaded to the blockchain for permanent record, and then the SP will store such authorization information and personal data. The DP generates corresponding authorization fingerprints based on the authorization information and stores them independently. Through the authorization information and authorization fingerprints on the chain, the DP can verify the authenticity of the authorization information stored by the SP at any time. Meanwhile, by leveraging the personal data fingerprint on the blockchain, the DP can check whether the personal data stored by the SP has been tampered with. Additionally, the scheme incorporates database technology to accelerate data query. We implemented a VAIMS prototype on Etherum, and experiments demonstrate that the scheme is effective. [ABSTRACT FROM AUTHOR]

In the digital age, data sovereignty has emerged as a critical concern due to the increasing demand for privacy, security, and user control. In this context, decentralized storage infrastructure is reshaping how data are stored and managed, leading the transition from traditional centralized models to a more decentralized and user-driven approach to data sovereignty, known as data self-sovereignty (DSS). This paper presents a systematic comparative analysis of decentralized storage systems, emphasizing their potential to enhance sustainable DSS. By highlighting the integral role of blockchain technology, this study critically examines various decentralized storage platforms, including Arweave, BitTorrent, Dat Protocol, Filecoin, Hypercore Protocol, IPFS, MaidSafe, Sia, Storj, and Swarm. The analysis covers the key architectural features of these systems, their performance metrics, and their contribution to user data sovereignty. This study aims to comprehensively explain how these decentralized storage solutions allow users to maintain complete control over their data, thus offering a viable alternative to traditional centralized storage methods. Therefore, This paper contributes to ongoing data sovereignty research and guides future developments in decentralized storage technologies. [ABSTRACT FROM AUTHOR]