Secure Data Exchange Research Articles

Enabling blockchain-IoT convergence for industrial revolution 4.0 innovation: A critical review

The Fourth Industrial Revolution (4IR) has revolutionised global interactions through the Internet of Things (IoT), connecting over 40 billion devices by 2030, raising significant security, protection, and privacy concerns. Blockchain technology offers a decentralised, secure, and transparent solution for data sharing and storage, leveraging its core characteristics—immutability, data integrity, transparency, and consensus—to enable tamper-proof records, real-time tracking, and secure data sharing in supply chain management and healthcare. Despite high implementation costs, blockchain-IoT convergence promises transformative benefits, including enhanced efficiency, reduced costs, and improved security. This study provides an in-depth analysis of blockchain's applications in IoT, highlighting its potential to enhance data security and privacy, improve supply chain management, facilitate secure healthcare data exchange, and enable real-time tracking and monitoring. Future research directions include scalability solutions, interoperability protocols, regulatory frameworks, blockchain-based supply chain management, and quantum-resistant blockchain networks.

Performance evaluation framework of MQTT client libraries for IoT applications in manufacturing

The Internet of Things (IoT) is a revolutionary technology in the field of manufacturing that enables real-time data communication and control of various industrial sensors and devices. MQTT (Message Queuing Telemetry Transport) is one of the most popular communication protocols for IoT applications which offers lightweight, efficient, and reliable communication. There are several MQTT client libraries available for implementing MQTT communication for IoT applications. The selection of an appropriate client library can significantly impact the performance of an IoT application. This paper presents a performance evaluation framework for MQTT client libraries for IoT applications in the manufacturing industry. This paper aims to create a standardized virtual testing environment to compare the performance of different MQTT client libraries using various test conditions. It offers a structured and standardized methodology for evaluating performance aspects such as latency, scalability, and resource utilization. By systematically evaluating the performance of MQTT client libraries against these metrics, users can make informed decisions while selecting the most appropriate library for their IoT applications. The framework takes into consideration the unique requirements and constraints of manufacturing applications, such as the need for low-latency communication, secure data exchange, and compatibility with resource-constrained devices. Ultimately, this research contributes to the optimization of IoT applications in the manufacturing industry, facilitating the implementation of efficient, reliable, and scalable data communication.

Hybridized Data Encoding based Encryption and Diffie Hellman Decryption for Security Enhancement

Information security is extremely important because the modification and interception of the data can lead to loss of data integrity, confidentiality, and availability. The encryption process is a critical component of classic standard encryption techniques such as advanced encryption, standard block ciphers, and data encryption standards. The traditional algorithm requires increased power consumption and memory. Therefore, there is a need to develop an efficient cryptographic operation to promote better security. The encryption process is performed using the Hybridized Data Encoding (HDE) model. Here, the optimal keys can be selected using the Chaotic Coati optimization algorithm (ChCoA). The decryption process can be performed using the Enhanced Diffie Hellman algorithm (EDHA). The resulting achievements will include effective encryption and decryption algorithms that together strengthen data security, facilitate secure data exchange, and provide superior protection against data vulnerabilities. By implementing the proposed work in the Matlab working platform, the performances in terms of encryption time, decryption time, processing time and throughput are analyzed. The proposed model achieved a throughput of 249.1093 (kb/s) and a processing time of 0.55 (sec).

Application of Attribute-Based Encryption in Military Internet of Things Environment.

The Military Internet of Things (MIoT) has emerged as a new research area in military intelligence. The MIoT frequently has to constitute a federation-capable IoT environment when the military needs to interact with other institutions and organizations or carry out joint missions as part of a coalition such as in NATO. One of the main challenges of deploying the MIoT in such an environment is to acquire, analyze, and merge vast amounts of data from many different IoT devices and disseminate them in a secure, reliable, and context-dependent manner. This challenge is one of the main challenges in a federated environment and forms the basis for establishing trusting relationships and secure communication between IoT devices belonging to different partners. In this work, we focus on the problem of fulfillment of the data-centric security paradigm, i.e., ensuring the secure management of data along the path from its origin to the recipients and implementing fine-grained access control mechanisms. This problem can be solved using innovative solutions such as applying attribute-based encryption (ABE). In this work, we present a comprehensive solution for secure data dissemination in a federated MIoT environment, enabling the use of distributed registry technology (Hyperledger Fabric), a message broker (Apache Kafka), and data processing microservices implemented using the Kafka Streams API library. We designed and implemented ABE cryptography data access control methods using a combination of pairings-based elliptic curve cryptography and lightweight cryptography and confirmed their suitability for the federations of military networks. Experimental studies indicate that the proposed cryptographic scheme is viable for the number of attributes typically assumed to be used in battlefield networks, offering a good trade-off between security and performance for modern cryptographic applications.

Secure Data Sharing in Decentralized Networks: Encryption Techniques, Access Control Mechanisms, and Data Integrity Verification

The introduction of decentralized systems in a rapidly changing technological world has introduced many issues and risks regarding privacy and secure data exchange. This paper addresses the complexities of secure data exchange within decentralized systems, focusing on encryption techniques, access control mechanisms, and data integrity verification. We begin by analyzing the impending risks and limitations within decentralized systems, including the potential for unauthorized access and data breaches from vulnerable points present in decentralized system entities. Subsequently, we analyze and explore modern methods of encryption to safeguard confidential data while also ensuring privacy. Furthermore, we examine access control strategies and integrity verification protocols, which play crucial roles in ensuring that data remains secure against unwarranted access and reliable across distributed ecosystems. Our findings emphasize the need for robust and intricate security measures adapted to the unique framework of decentralized systems. This study aims to advance the understanding of privacy and security in decentralized systems while serving as a stepping stone and valuable resource for future research.

An edge computing and distributed ledger technology architecture for secure and efficient transportation

Intelligent Transportation Systems (ITS) faces significant challenges in achieving its goal of sustainable and efficient transportation. These challenges include real-time data processing bottlenecks caused by high communication latency and security vulnerabilities related to centralized data storage. We propose a novel architecture that leverages Edge Computing and Distributed Ledger Technology (DLT) to address these concerns. Edge computing pushes cloud services, such as vehicles and roadside units, closer to the data source. This strategy reduces latency and network congestion. DLT provides a secure, decentralized platform for storing and sharing ITS data. Its tamper-proof nature ensures data integrity and prevents unauthorized access. Our architecture utilizes these technologies to create a decentralized platform for ITS data management. This platform facilitates secure processing, storage, and data exchange from various sources in the transportation network. This paper delves deeper into the architecture, explaining its essential components and functionalities. Additionally, we explore its potential applications and benefits for ITS. We describe a case study focusing on a data marketplace system for connected vehicles to assess the architecture’s effectiveness. The simulation results show an average latency reduction of 83.35% for publishing and 87.57% for purchasing datasets compared to the cloud architecture. Additionally, transaction processing speed improved by 18.73% and network usage decreased by 96.67%. The proposed architecture also achieves up to 99.61% reduction in mining centralization.

Proof-of-resource: A resource-efficient consensus mechanism for IoT devices in blockchain networks

In this paper, we propose an innovative, lightweight, and energy-efficient consensus mechanism, Proof-of-Resource (PoR), custom-designed for Internet of Things (IoT) devices in blockchain networks. As IoT's integration with blockchain faces hurdles such as scalability, resource efficiency, and security, conventional blockchain consensus mechanisms prove unsuitable due to IoT devices' resource limitations. The PoR is a breakthrough that capitalizes on IoT device resources' inherent capabilities to achieve consensus, thus enabling secure and efficient data exchange while minimizing resource consumption. Our paper presents the comprehensive design of PoR, discussing aspects like initialization, resource verification, consensus protocol, validator selection, block validation, and rewards. Through a simulation involving fifteen IoT devices, we demonstrate that PoR effectively addresses key challenges in IoT-blockchain integration, signifying a significant step forward in enabling blockchain technology for IoT systems.

Leveraging digital data spaces in purchasing and supply management: Paving the way to the circular economy exemplified by Catena-X

The transition to a circular economy (CE) is increasing the complexity of data processing for purchasing and supply management (PSM), necessitating the adoption of digital technologies. In particular, digital data spaces (DDSs) have gained prominence for facilitating data sharing and collection and allowing secure data exchange. This study explores the information processing capabilities critical for PSM when using DDSs. Using a single case study research design, the study focuses on the DDS Catena-X. Through 20 semi-structured interviews with experts from 12 participating companies, the research explores organizational information processing theory as a theoretical foundation. The results show that DDSs support PSM within the CE by connecting the various actors and through extensive data exchange along the value chain. In addition, the findings identify two critical sets of information capabilities necessary for the effective use of DDSs in PSM: inter-organizational process capabilities and inter-organizational IT-based capabilities. This study contributes to theoretical knowledge within the supply chain management domain by 1) exploring how DDSs benefit the informational capabilities of PSM in CE, 2) investigating the inter-organizational capabilities PSM needs to fully leverage DDSs while 3) introducing the OIPT to the field of circular PSM utilizing DDSs.

Securing Data Exchange with Elliptic Curve Cryptography: A Novel Hash-Based Method for Message Mapping and Integrity Assurance

To ensure the security of sensitive data, elliptic curve cryptography (ECC) is adopted as an asymmetric method that balances security and efficiency. Nevertheless, embedding messages into elliptic curve (EC) points poses a significant challenge. The intricacies of this process can greatly affect the overall security and efficiency of the cryptosystem, reflecting security vulnerabilities observed in many existing schemes that utilize ElGamal ECC-based encryption. In this paper, we introduce an innovative hash-based technique for securely embedding messages into EC points before encryption. A random parameter and a shared secret point generated through the EC Diffie–Hellman protocol are used to bolster the scheme’s security. The security of the proposed method is evaluated against various attack models; moreover, the complexity, and sensitivity of the encryption scheme, as well as its inputs, are analyzed. The randomness assessment of the ciphertext was performed using the NIST statistical test suite. Additionally, we propose a mechanism to ensure the integrity of the message by securely appending a tag to the ciphertext. As a consequence, a comprehensive analysis of our scheme demonstrates its effectiveness in maintaining data security and integrity against various attack models. The algorithm also meets more criteria such as the strict avalanche criterion, linear complexity, and operability.

Advancing Road Safety through Cloud Based RSU Solutions for Smart Internet of Vehicles

This research proposes a system to improve road safety by detecting and alerting drivers about hazardous road conditions in real-time. Vehicles equipped with sensors, GPS, and communication devices can autonomously detect hazardous road conditions and transmit alerts to a central cloud system through IoT MQTT protocol. Upon receiving alerts, vehicles can dynamically adjust their routes to avoid hazardous areas, reducing the risk of accidents. By utilizing IoT technology, the system ensures the reliability and authenticity of shared information, enhancing trust and overall road safety awareness. The proposed system architecture leverages cloud-based Roadside Units (RSUs) to facilitate communication among smart vehicles, providing real-time road condition information and ensuring secure and efficient data exchange. The system aims to address the challenges of existing IoV frameworks, such as data protection, key management, storage, concurrency performance, and response speed, by implementing robust security measures and efficient data management strategies.

A blockchain technology for improving financial flows in humanitarian supply chains: benefits and challenges

Purpose This study aims to determine how the applications of blockchain technology (BT) can play a crucial role in managing financial flows in the humanitarian supply chain (HSC) and what benefits and challenges are associated with BT in a humanitarian setting. Design/methodology/approach The present study used a qualitative research approach, incorporating a systematic literature review and conducting semi-structured interviews with 12 experts in the fields of humanitarian operations, supply chain management, fintech and information technology. Findings The findings show that the humanitarian sector has the potential to reap significant benefits from BT, including secure data exchange, efficient SCM, streamlined donor financing, cost-effective financial transactions, smooth digital cash flow management and the facilitation of cash programs and crowdfunding. Despite the promising prospects, this study also illuminated various challenges associated with the application of BT in the HSC. Key challenges identified include scalability issues, high cost and resource requirements, lack of network reliability, data privacy, supply chain integration, knowledge and training gaps, regulatory frameworks and ethical considerations. Moreover, the study highlighted the importance of implementing mitigation strategies to address the challenges effectively. Research limitations/implications The present study is confined to exploring the benefits, challenges and corresponding mitigation strategies. The research uses a semi-structured interview method as the primary research approach. Originality/value This study adds to the existing body of knowledge concerning BT and HSC by explaining the pivotal role of BT in improving the financial flow within HSC. Moreover, it addresses a notable research gap, as there is a scarcity of studies that holistically cover the expert perspectives on benefits, challenges and strategies related to blockchain applications for effective financial flows within humanitarian settings. Consequently, this study seeks to bridge this knowledge gap and provide valuable insights into this critical area.

BLOCKCHAIN TECHNOLOGY IN SUPPLY CHAIN MANAGEMENT

This paper aims to fill the gap in existing research by examining the impact of blockchain technology on supply chain management, particularly its ability to retrospectively trace events in the chain. For example, in pharmaceuticals, blockchain automatically records information like expiration dates, reducing the need for human involvement. By implementing this backward technology, we've simplified processes for suppliers and manufacturers, allowing the system to identify defective or expired items autonomously, saving time and costs. Previously, the supply chain operated as a one-way system without return options, but now, with blockchain integration, relevant parties are informed about necessary replacements from the manufacturer's end. Blockchain's integration into supply chain management is a significant advancement, offering unparalleled transparency, traceability, and security in logistics and distribution. This article explores how blockchain can revolutionize established supply chain practices, delving into applications like tracing goods from origin to destination, using smart contracts for automated agreements, and secure data exchange while protecting privacy. Case studies highlight advantages such as reduced expenses, risks, and improved compliance. Blockchain, as a decentralized ledger system, provides instant, unchangeable record-keeping and cryptographic validation, instilling confidence among stakeholders. In supply chain management, this means identifiable product origins, better tracking, less fraud, and quicker dispute resolution. However, challenges like scalability, energy use, and network interoperability exist, underscoring the need for industry collaboration and standardization efforts

A Secure Data Publishing and Access Service for Sensitive Data from Living Labs: Enabling Collaboration with External Researchers via Shareable Data

Intending to enable a broader collaboration with the scientific community while maintaining privacy of the data stored and generated in Living Labs, this paper presents the Shareable Data Publishing and Access Service for Living Labs, implemented within the framework of the H2020 VITALISE project. Building upon previous work, significant enhancements and improvements are presented in the architecture enabling Living Labs to securely publish collected data in an internal and isolated node for external use. External researchers can access a portal to discover and download shareable data versions (anonymised or synthetic data) derived from the data stored across different Living Labs that they can use to develop, test, and debug their processing scripts locally, adhering to legal and ethical data handling practices. Subsequently, they may request remote execution of the same algorithms against the real internal data in Living Lab nodes, comparing the outcomes with those obtained using shareable data. The paper details the architecture, data flows, technical details and validation of the service with real-world usage examples, demonstrating its efficacy in promoting data-driven research in digital health while preserving privacy. The presented service can be used as an intermediary between Living Labs and external researchers for secure data exchange and to accelerate research on data analytics paradigms in digital health, ensuring compliance with data protection laws.

Streamlining IoT-driven Data Using Blockchain

The integration of Internet of Things (IoT) technology has revolutionized data collection and analytics, creating vast networks of interconnected devices generating large volumes of data. However, this rapid expansion of IoT ecosystems introduces significant challenges related to data security, integrity, scalability, and privacy. Blockchain technology, with its decentralized and immutable nature, emerges as a compelling solution to address these challenges. This paper explores the synergy between IoT and blockchain, examining how blockchain can streamline IoT-driven data by providing secure data exchanges, enhancing transparency, and facilitating scalability. The study investigates the key mechanisms through which blockchain can mitigate common IoT data issues. It considers blockchain's role in ensuring data integrity by utilizing cryptographic methods, enabling traceability through distributed ledgers, and protecting against unauthorized data manipulation. Furthermore, it explores the potential of blockchain-based smart contracts to automate processes and improve interoperability among IoT devices. The paper delves into specific use cases, such as smart cities, demonstrating how blockchain can effectively streamline IoT data across various industries. The findings highlight that while blockchain offers substantial benefits, it also introduces unique challenges, including high energy consumption, latency concerns, and complex integration processes. This concludes with a discussion of Security concerns, Comparison with existing solutions. By addressing these challenges, blockchain can become a pivotal technology in streamlining IoT-driven data, paving the way for more secure, efficient, and trustworthy IoT ecosystems.

Multi-task learning for PBFT optimisation in permissioned blockchains

Finance, supply chains, healthcare, and energy have an increasing demand for secure transactions and data exchange. Permissioned blockchains fulfilled this need thanks to the consensus protocol that ensures that participants agree on a common value. One of the most widely used protocols in private blockchains is the Practical Byzantine Fault Tolerance (PBFT), which tolerates up to one-third of Byzantine nodes, performs within partially synchronous systems, and has superior throughput compared to other protocols. It has, however, an important bandwidth consumption: 2N(N−1) messages are exchanged in a system composed of N nodes to validate only one block.It is possible to reduce the number of consensus participants by restricting the validation process to nodes that have demonstrated high levels of security, rapidity, and availability. In this paper, we propose the first database that traces the behavior of nodes within a system that performs PBFT consensus. It reflects their level of security, rapidity, and availability throughout the consensus. We first investigate different Single-Task Learning (STL) techniques to classify the nodes within our dataset. Then, using Multi-Task Learning (MTL) techniques, the results are much more interesting, with classification accuracies over 98%. Integrating node classification as a preliminary step to the PBFT protocol optimizes the consensus. In the best cases, it is able to reduce the latency by up to 94% and the communication traffic by up to 99%.

Multi-Device Security Application for Unmanned Surface and Aerial Systems

The use of autonomous and unmanned systems continues to increase, with uses spanning from package delivery to simple automation of tasks and from factory usage to defense industries and agricultural applications. With the proliferation of unmanned systems comes the question of how to secure the command-and-control communication links among such devices and their operators. In this work, we look at the use of the Messaging Layer Security (MLS) protocol, designed to support long-lived continuous sessions and group communication with a high degree of security. We build out MAUI—an MLS API for UxS Integration that provides an interface for the secure exchange of data between a ScanEagle unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV) in a multi-domain ad-hoc network configuration, and experiment on system limits such as the ciphersuite set-up time and message handling rates. The experiments in this work were conducted in virtual and physical environments between the UAV, USV, and a controller device (all of different platforms). Our results demonstrate the viability of capitalizing on MLS’s capabilities to securely and efficiently transmit data for distributed communication among various unmanned system platforms.

Blockchain Interoperability in Data Exchange Logistics Integration

Logistics companies are increasingly adopting private blockchains for enhanced data management because of the trends in cooperation. Nevertheless, this practice poses new challenges concerning the security and sharing of data. The real-time nature and diversity of logistics data increase the difficulty of protecting the data. Additionally, when transportation information changes, downstream enterprises must promptly adjust their production plans to accommodate these alterations. The strict access controls of private blockchains can obstruct downstream enterprises from obtaining data, posing a challenge to the overall operational efficiency. In this paper, we propose an innovative logistics data protection scheme that employs private set intersection (PSI) and blockchain cross-chain technology to achieve data security. In our scheme, logistics companies within the logistics consortium are added as trusted agents to the public blockchain, enabling downstream enterprises to acquire logistics data integration from the public blockchain. Utilizing an RSA-based PSI protocol, our approach enhances exchange efficiency while protecting private data without transmitting additional information. We evaluate the performance of the proposed solution through a series of experiments, and the results demonstrate that our solution can achieve secure and efficient logistics data exchange.

Communication Protocols for IoT Applications

Abstract: The Internet of Things (IoT) can be defined as an ecosystem of interconnected devices such as sensors, microcontrollers, actuators that enable them to communicate and share information between them through internet for making the system intelligent and smart. As there is growth in IoT, communication protocols play a pivotal role in facilitating efficient, reliable, and secure data exchange between these components. Through this analysis, guidance is provided to users to choose particular protocol according to the application. Communication protocols in IoT offers a varied set of options which are designed for specific use cases.

End to End secure data exchange in value chains with dynamic policy updates

Data exchange among value chain partners offers a competitive advantage, but it also exposes sensitive data to increasing risks of compromise. To protect this data, securing it during storage and transmission is essential, allowing only the data producer and final consumer to access or modify it. This can be particularly challenging for Industrial Internet of Things (IIoT) devices, which often have limited processing and memory capabilities. To address these challenges, End-to-End (E2E) security mechanisms are needed to prevent data breaches resulting from value chain attacks. Additionally, value chain environments are dynamic and involve multiple data generation and consumption entities, requiring the ability to update access policies as needed. This paper presents a Ciphertext-Policy Attribute-Based Encryption (CP-ABE) data exchange system that provides E2E security for value chains, considering the most relevant security and industrial requirements. The proposed solution can protect data according to access policies while also allowing those policies to be updated without breaking E2E security or overloading field devices. The experimental evaluation demonstrates the feasibility of the proposed solution for IIoT platforms.

Blockchain integration in healthcare: a comprehensive investigation of use cases, performance issues, and mitigation strategies.

Healthcare is a critical area where blockchain technology (BT) is being heralded as a potential game-changer for facilitating secure and efficient data sharing. The purpose of this review is to examine BT applications, performance challenges, and solutions in healthcare. To begin, This review paper explores popular blockchain networks for data exchange, encompassing both public and permissioned platforms, such as Ethereum and Hyperledger Fabric. This paper analyzes the potential applications of BT's decentralized, immutable, and smart contract capabilities in healthcare settings, including secure and interoperable health data exchange, patient consent management, drug supply chain oversight, and clinical trial management. The healthcare industry might greatly benefit from the increased privacy, transparency, and accessibility that these technologies provide. Despite BT's promising medical uses, the technology is not without its drawbacks. High energy consumption, throughput, and scalability are all concerns. We wrapped up by discussing the solutions that have been implemented, including consensus processes, scalability measures like sharding, and off-chain transactions that are designed to mitigate the drawbacks.