This paper presents a Deep Reinforcement Learning (DRL) based Internet of Things (IoT)-enabled Prism blockchain. The recent advancements in the field of IoT motivate the development of a secure infrastructure for storing and sharing vast amounts of data. Blockchain, a distributed and immutable ledger, is best known as a potential solution to data security and privacy for the IoT. The scalability of blockchain, which should optimize the throughput and handle the dynamics of the IoT environment, becomes a challenge due to the enormous amount of IoT data. The critical challenge in scaling blockchain is to guarantee decentralization, latency, and security of the system while optimizing the transaction throughput. This paper presents a DRL-based performance optimization for blockchain-enabled IoT. We consider one of the recent promising blockchains, Prism, as the underlying blockchain system because of its good performance guarantees. We integrate the IoT data into Prism blockchain and optimize the performance of the system by leveraging the Proximal Policy Optimization (PPO) method. The DRL method helps to optimize the blockchain parameters like mining rate and mined blocks to adapt to the environment dynamics of the IoT system. Our results show that the proposed method can improve the throughput of Prism blockchain-based IoT systems while preserving Prism performance guarantees. Our scheme can achieve 1.5 times more system rewards than IoT-integrated Prism. In our experimental setup, the proposed scheme could improve the average throughput of the system by about 6,000 transactions per second compared to Prism.
Jummai Enare Abang, Haifa Takruri, Rabab Al-Zaidi, Mohammed Al-Khalidi
Blockchain is a decentralized and distributed ledger technology that enables secure and transparent recording of transactions across multiple participants. Hyperledger Fabric (HLF), a permissioned blockchain, enhances performance through its modular design and pluggable consensus. However, integrating HLF with enterprise applications introduces latency challenges. Researchers have proposed numerous latency performance modelling techniques to address this issue. These studies contribute to a deeper understanding of HLF’s latency by employing various modelling approaches and exploring techniques to improve network latency. However, existing HLF latency modelling studies lack an analysis of how these research efforts apply to specific use cases. This paper examines existing research on latency performance modelling in HLF and the challenges of applying these models to HLF-enabled Internet of Things (IoT) use cases. We propose a novel set of criteria for evaluating HLF latency performance modelling and highlight key HLF parameters that influence latency, aligning them with our evaluation criteria. We then classify existing papers based on their focus on latency modelling and the criteria they address. Additionally, we provide a comprehensive overview of latency performance modelling from various researchers, emphasizing the challenges in adapting these models to HLF-enabled IoT blockchain within the framework of our evaluation criteria. Finally, we suggest directions for future research and highlight open research questions for further exploration.
Syed Thouheed Ahmed, T R Mahesh, E. Srividhya, V. Vinoth Kumar · 7 authors
Categorizing Artificial Intelligence of Medical Things (AIoMT) devices within the realm of standard Internet of Things (IoT) and Internet of Medical Things (IoMT) devices, particularly at the server and computational layers, poses a formidable challenge. In this paper, we present a novel methodology for categorizing AIoMT devices through the application of decentralized processing, referred to as "Federated Learning" (FL). Our approach involves deploying a system on standard IoT devices and labeled IoMT devices for training purposes and attribute extraction. Through this process, we extract and map the interconnected attributes from a global federated cum aggression server. The aim of this terminology is to extract interdependent devices via federated learning, ensuring data privacy and adherence to operational policies. Consequently, a global training dataset repository is coordinated to establish a centralized indexing and synchronization knowledge repository. The categorization process employs generic labels for devices transmitting medical data through regular communication channels. We evaluate our proposed methodology across a variety of IoT, IoMT, and AIoMT devices, demonstrating effective classification and labeling. Our technique yields a reliable categorization index for facilitating efficient access and optimization of medical devices within global servers.
Roger Lacson, Yufei Yu, Tsung-Ting Kuo, Lucila Ohno‐Machado
OBJECTIVE: Blockchain has emerged as a potential data-sharing structure in healthcare because of its decentralization, immutability, and traceability. However, its use in the biomedical domain is yet to be investigated comprehensively, especially from the aspects of implementation and evaluation, by existing blockchain literature reviews. To address this, our review assesses blockchain applications implemented in practice and evaluated with quantitative metrics. MATERIALS AND METHODS: This systematic review adapts the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to review biomedical blockchain papers published by August 2023 from 3 databases. Blockchain application, implementation, and evaluation metrics were collected and summarized. RESULTS: Following screening, 11 articles were included in this review. Articles spanned a range of biomedical applications including COVID-19 medical data sharing, decentralized internet of things (IoT) data storage, clinical trial management, biomedical certificate storage, electronic health record (EHR) data sharing, and distributed predictive model generation. Only one article demonstrated blockchain deployment at a medical facility. DISCUSSION: Ethereum was the most common blockchain platform. All but one implementation was developed with private network permissions. Also, 8 articles contained storage speed metrics and 6 contained query speed metrics. However, inconsistencies in presented metrics and the small number of articles included limit technological comparisons with each other. CONCLUSION: While blockchain demonstrates feasibility for adoption in healthcare, it is not as popular as currently existing technologies for biomedical data management. Addressing implementation and evaluation factors will better showcase blockchain's practical benefits, enabling blockchain to have a significant impact on the health sector.
As blockchain becomes more widely used, a growing number of application fields are becoming interested in blockchain to benefit from its decentralised nature, invariability, security, transparency, quick transaction capabilities, and cost-effectiveness. Blockchain has a wide range of applications and uses in healthcare. Distributed ledger technology facilitates the secure transfer of patient medical records, manages the medicine supply chain, and creates an efficient, transparent, safe, and effective way of communicating data across global healthcare. The organ transplantation process (OTP) is one of the healthcare areas that benefit from the use of such technology to make its process more secure and transparent. In this article, we put forward a systematic literature review analysis on the application of blockchain to the OTP. Additionally, we address and highlight the barriers and challenges that arise while using blockchain technology for the OTP. We also offer some suggestions for future developments that would enhance blockchain’s implementation in the OTP domain.
Artificial intelligence (AI) and blockchain technology have emerged as increasingly prevalent and influential elements shaping global trends in Information and Communications Technology (ICT). Namely, the synergistic combination of blockchain and AI introduces beneficial, unique features with the potential to enhance the performance and efficiency of existing ICT systems. However, presently, the confluence of these two disruptive technologies remains in a rather nascent stage, undergoing continuous exploration and study. In this context, the work at hand offers insight regarding the most significant features of the AI and blockchain intersection. Sixteen outstanding, recent articles exploring the combination of AI and blockchain technology have been systematically selected and thoroughly investigated. From them, fourteen key features have been extracted, including data security and privacy, data encryption, data sharing, decentralized intelligent systems, efficiency, automated decision systems, collective decision making, scalability, system security, transparency, sustainability, device cooperation, and mining hardware design. Moreover, drawing upon the related literature stemming from major digital databases, we constructed a timeline of this technological convergence comprising three eras: emerging, convergence, and application. For the convergence era, we categorized the pertinent features into three primary groups: data manipulation, potential applicability to legacy systems, and hardware issues. For the application era, we elaborate on the impact of this technology fusion from the perspective of five distinct focus areas, from Internet of Things applications and cybersecurity, to finance, energy, and smart cities. This multifaceted, but succinct analysis is instrumental in delineating the timeline of AI and blockchain convergence and pinpointing the unique characteristics inherent in their integration. The paper culminates by highlighting the prevailing challenges and unresolved questions in blockchain and AI-based systems, thereby charting potential avenues for future scholarly inquiry.
Blockchain, on the other hand, is a groundbreaking technology that provides a distributed and Decentralized environment in which nodes in a list of networks can connect to each other without the need for a central authority. It has the potential to overcome the limits of Electronic Health Record (EHR) management and create a more secure, Decentralized, and safer environment for exchanging EHR data. Further, blockchain is a distributed ledger on which data can be stored and shared in a cryptographically secure, validated, and mutually agreed-upon manner across all mining nodes. The blockchain stores data with a high level of integrity and robustness, and it cannot be altered. Electronic health records (EHRs) are digitally saved health records that provide information about a person’s health. EHRs are generally shared among healthcare stakeholders, and thus are susceptible to power failures, data misuse, a lack of privacy, security, and an audit trail, among other problems. The aim of our proposed framework is firstly to implement blockchain technology for EHR and secondly to provide secure storage of electronic records by defining granular access rules for the users of the proposed framework. Moreover, this framework also discusses the scalability problem faced by the blockchain technology in general via use of off-chain storage of the records. This framework provides the EHR system with the benefits of having a scalable, secure and integral blockchain-based solution.
Blockchain applications often rely on lightweight clients to access and verify on-chain data efficiently without the need to run a resource-intensive full node. These light clients must maintain robust security to protect the blockchain's integrity for users of applications built upon it, achieving this with minimal resources and without significant latency. Moreover, different applications have varying security needs. This work focuses on addressing these two key requirements in the context of Proof-of-Stake (PoS) blockchains and identifying the fundamental cost-latency trade-offs to achieve tailored, optimal security for each light client. The key security guarantee of PoS blockchains is economic (implied by the "stake"). In this paper we formalize this cryptoeconomic security to light clients, ensuring that the cost of corrupting the data provided to light clients must outweigh the potential profit, thereby economically deterring malicious actors. We further introduce "insured" cryptoeconomic security to light clients, providing unconditional protection via the attribution of adversarial actions and the consequent slashing of stakes. The divisible and fungible nature of stake facilitates programmable security, allowing for customization of the security level and insurance amount according to the specific needs of different applications. We implemented the protocols in less than 1000 lines of Solidity and TypeScript code and evaluated their gas cost, latency, and the computational overhead. For example, for a transaction with value of \$32k, the light client can choose between zero cost with a latency of 5 hours or instant confirmation with an insurance cost of \$7.45. Thus, the client can select the optimal point on the latency-cost trade-off spectrum that best aligns with its needs. Light clients require negligible storage and face minimal computational costs,...
Block Chain is one of the technologies that is gaining popularity in the modern world. The technology in question offers an exceptionally robust level of protection. Users do not have a lot of information about Block Chain, but its security is used to safeguard the data that is sent in several directions. This user continued to utilize the “ChaCha” and RBJ25 algorithms, which are considered to be compact and secure varieties. In this article, we present the new security mechanism that we have decided to call RPBB24-1. Two components make up the RPBB-24-1 approach, which are encryption and decryption. Five stages are involved in the encryption procedure. Assignment of the “Latin Alphabet cod” to PT is the first step in the procedure. Multiplying the number by itself four times using Equation (1) is the second step. Using encrypted data, the third procedure involves swapping the cell values, but the process begins with the 0th cell value from the most recent cell value. The fourth step involves dividing the prime key into the values of the matrix cells. Implementing the “ChaCha” algorithm in the matrix is the fifth step in the procedure. At long last, the ordinary text is transformed into encrypted text. Unlike the encryption procedure, the decryption approach works in the opposite direction. When compared to the approach that is currently in use, the suggested method offers a higher level of security.
Vehicular Edge Computing (VEC) has emerged as a promising paradigm to enable low-latency Vehicle-to-Everything (V2X) services by bringing computing resources closer to vehicles. However, the high dynamicity of vehicular networks poses significant challenges in designing an optimal policy for delivering V2X services while ensuring security and timely service delivery. To address these challenges, this paper proposes a BlockchainEnabled Vehicular Edge Computing (BEVEC) framework that employs a dual-layer verification process empowered with a permissioned blockchain to ensure data accuracy and integrity. A novel system utility function is designed to measure the performance of the BEVEC, which also serves as the basis for a consensus mechanism of the permissioned blockchain. To optimize this utility, a Deep Reinforcement Learning (DRL) algorithm is proposed to enable timely service delivery in BEVEC. Simulation-based results demonstrate the effectiveness of the proposed algorithm when compared to existing approaches. On average, it obtained an 18% reduction in latency, a 38% improvement in successful service delivery, and a 65% decrease in energy consumption.
In this paper, we present a novel Secure Clustering Routing Method based on Blockchain and Swarm Intelligence (BS-SCRM) for Wireless Sensor Networks (WSNs), which serves as a cornerstone in the Internet of Things (IoT) infrastructure. Recognizing the limitations of existing clustering routing methods in addressing security threats, our approach integrates blockchain technology to fortify WSNs against vulnerabilities such as man-in-the-middle attacks. The proposed BS-SCRM method is structured in two phases: (1) an enhanced cluster head (CH) election utilizing an elite strategy-enhanced Whale Optimization Algorithm (WOA) that considers node energy and proximity to the base station, and (2) a secure data on-chain phase where blockchain comes into play, encrypting and validating cluster data to safeguard integrity and prevent tampering. We further tackle the challenge of implementing blockchain in resource-constrained WSNs by assigning distinct roles to devices, i.e., ordinary nodes with data viewing permissions and accounting nodes entrusted with both data viewing and consensus algorithm execution. Extensive simulations confirm that BS-SCRM not only improves clustering quality but also provides a more secure and energy-efficient routing solution compared to contemporary methods. More specifically, simulation results in different scenarios demonstrate that BS-SCRM enhances network lifetime by 24-73% compared to other clustering methods when facing attacks.
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.
Energy systems are currently undergoing a transformation towards new paradigms characterized by decarbonization, decentralization, democratization, and digitalization. In this evolving context, energy blockchain, aiming to enhance efficiency, transparency, and security, emerges as an integrated technological solution designed to address the diverse challenges in this field. Data security is essential for the reliable and efficient functioning of energy blockchain. The pressing need to address challenges related to secure data storage, effective data management, and efficient data utilization is increasingly vital. This paper offers a comprehensive survey of academic discourse on energy blockchain data security over the past five years, adopting an all-encompassing perspective that spans data storage, management, and utilization. Our work systematically evaluates and contrasts the strengths and weaknesses of various research methodologies. Additionally, this paper proposes an integrated hierarchical on-chain and off-chain security energy blockchain architecture, specifically designed to meet the complex security requirements of multi-blockchain business environments. Concludingly, this paper identifies key directions for future research, particularly in advancing the integration of storage, management, and utilization of energy blockchain data security.
In today’s world almost all hospital uses hardcopy for patient data store and for booking appointment. All patient data is available on paper and user need to manage that all over he goes. Consider ’A’ patient got admitted in City Pune, all his data is stored on paper and what medicines he took. All the info about his health is stored there. After someday ‘A’ patient gone to another city far away without carrying any documents and there he got and health emergency and is not in condition of speaking and need urgently help. But due to lack of info available about patient doctor could not urgently take decisions. So, to reduce this risk our system is developed. The distribution of Health records becomes a time consuming and expensive process when we use the traditional client-server healthcare data management system where each hospital/clinic maintains its own database of patients’ medical records. A patient’s treatment is further delayed if the patient moves from one hospital to another hospital across different regions or countries. Moreover, most of the time a patient must repeat several laboratory and radiology tests. So, to address this the patient’s medical data from different hospitals are stored in a Blockchain based storage making it easily accessible by patients and the hospitals. And the pharma company will be able to store the information of medicines and medicals will be available to verify the medicines if they are from trustworthy companies. Keyword - - Dapp, Web3.Js, CSS.
In the quickly developing landscape of Web3.0, ensuring the security and integrity of digital documents has become paramount. This abstract introduces a groundbreaking solution, "Web3.0 Document Security: Leveraging Blockchain Technology," which harnesses the power of blockchain to revolutionize document transmission and protection. This innovative system leverages the inherent characteristics of blockchain, such as immutability, transparency, and decentralization, to develop a secured and sealed environment for the exchange of digital documents. By utilizing smart contracts, cryptographic hashing, and decentralized storage, this application guarantees the confidentiality, integrity, and authenticity of documents in an interconnected Web3.0 world. This paper provides an overview of the key features, benefits, and implications of adopting a decentralized application as the foundation for secure document transmission in the era of Web3.0 . Keywords— Documents, Data Security, Data Integrity, Secure Transmission, Cryptography, Blockchain, Cloud Technology, Web3
IoT systems are widely used in various applications, including healthcare, agriculture, manufacturing, and smart cities. However, these systems still have limitations, such as lack of security, high latency, energy inefficiency, the inefficiency of bandwidth utilization, and shortage of automaticity. The integration of edge computing and blockchain into IoT has been proposed to address these limitations. Yet, this integration is challenging and has not been deeply investigated. This paper aims to conduct a review of the integration of edge computing and blockchain into IoT systems. To the best of our knowledge, this is the first review paper that covers all aspects of system architectures and categories of blockchain-based edge deployment, complete security requirements, including confidentiality, integrity, authentication, authorization/access control, privacy, trust/confidence, transparency, availability, secure automaticity, and tolerance, and applications of blockchain-based edge potential usages with consideration of security requirements. Additionally, this review provides comprehensive discussions of challenges and insights into the future direction of blockchain-based edge IoT systems. The review aims to serve as an entry point for non-expert readers and researchers to various aspects of blockchain-based edge IoT systems.
Dorothy Gatwiri Bundi, Stephen Mutua, Simon Karume
This study of the literature delves into the complex area of medical systems interoperability, focusing on mitigating variables that impact security and data transfer at the structural and semantic levels. In the era of digital healthcare, the secure sharing of medical data is crucial, and this study looks at how Distributed Ledger Technologies (DLTs) can play a major role in addressing these challenges. Complex interoperability issues that come from differences in communication protocols, data formats, established data structures, data models, and data meaning and codification methodologies face the healthcare industry. These problems typically impede the seamless transmission of electronic medical records between healthcare systems. Because of their decentralized structure and cryptographic foundation, DLTs offer a workable solution to these issues. By critically evaluating previous research and case studies, DLTs may be able to lessen these interoperability issues, as this literature review illustrates. Since DLTs provide an immutable and secure platform for the transmission of medical data, guaranteeing data integrity and confidentiality, they are a natural fit for the sensitive nature of healthcare data. Their importance in creating safe communication protocols, enhancing the meaning of data, and defining models and formats for data is emphasized in this review. A comprehensive architecture for DLT interoperability in healthcare is also recommended by the research. This framework encourages the development of DLT integration, shared data models, standardized data formats, and governance and policy. By implementing this strategy and strengthening secure medical data sharing, healthcare organizations and governments may increase the efficiency, precision, and speed of healthcare delivery. The crucial role that DLTs play in removing the structural and semantic barriers to safe medical systems interoperability is highlighted in the conclusion of this literature review. By adopting DLTs, the healthcare sector may usher in a new era of standardized, safe, and efficient medical data transmission, which will ultimately benefit both patients and healthcare providers. This study shows how distributed ledger technologies (DLTs) have the potential to revolutionize the healthcare industry by enabling the secure and meaningful exchange of medical data between different systems, thereby improving patient care and healthcare outcomes.
Rawabi Aldossri, Ahmed Aljughaiman, Abdullah Albuali
This paper presents a systematic literature review investigating the integration of lightweight blockchain and fog computing technologies to enhance the security and operational efficiency of drones. With a focus on critical applications such as military surveillance and emergency response, this review examines how the combination of blockchain’s secure, decentralized ledger and fog computing’s low-latency, localized data processing can address the unique challenges of drone operations. By compiling and analyzing current research, this study highlights innovative approaches and solutions that leverage these technologies to improve data integrity, reduce communication latency, and facilitate real-time decision-making in drone missions. Our findings underscore the significant potential of this technological integration to advance the capabilities and reliability of drones in high-stakes scenarios.
The current period of medicine using digital technology for patient care presents a new level of integration of monitoring devices with the cloud computing environment that enables the collection, storage and access to data in ways that were never possible earlier. As the obvious part of this development, it is worth noting that the objective of such innovation is mostly on the integrity of data, provenance and security. Data integrity from as well as security of the Internet connected healthcare devices should be assured in the first place to keep patient safety and protect data privacy along with improve data-based decision-making. The centralized system and crowded nature of the current equipment are susceptible to single point of failure, data breach and potential manipulations of data, which raise questions and create doubts with regards data management processes pertaining to medical device systems. This work is addressed to the analysis of a novel security system based on blockchain that guarantees the implementation of a high performance with the solution of two medical device integrity and provenance safety issues in the cloud ecosystem. Fundamentally differentiating from the centralized systems that exist today, blockchain technology that is based on distributed database architectures, immutable logs, and consensus mechanisms provides for a new way to bring reliability and traceability to the entire medical device data chain. The suggested procedure is based on properties of blockchain technology. Such a solution can help to provide a clear and secure audit trail for medical devices. Storing, securing and accessing the device data can be carried out credibly, maintaining these data’s integrity and provenance. Ultimately, the solution, rely on the implementation of smart contracts, cryptocurrency processes, and the confidentiality and privacy of data, can be the answer which make up the practice of secure data sharing, data accessing and complying with regulations. The journal creates a modular system combining Medical devices, a cloud platform, and Blockchain solution. The architecture is intended to display the blockchain network's essential components, data validation and access control, and secure data storage mechanisms. Furthermore, the recommended solution implies state-of- the-art security tools, such as data encryption, access control, and abidance by regulatory systems, including HIPAA and GDPR. Implementation of an actual scenario of the proof-of-concept and performance evaluation are done to show the efficiency and performance of the blockchain-based solution provided. The results suggest that the proposed solution can establish the data reliability level, record all the various versions of modifications, and strengthen the security and transparency of medical device data processing in cloud computing. Through the exploration of the applications of blockchain for medical data management that this study proposes, we are laying the foundations of a future healthcare environment, which is expected to be more secure and trustworthy, where the sensor data of medical devices can be reliably controlled and accessed without jeopardizing the patient's safety or data privacy. To a great extent, the suggested solution can contribute to building trust in the digital tools utilized in health care, leading to more well-informed clinical decisions and ultimately improving the patients' results.
Extensive research on Nakamoto-style consensus protocols has shown that network delays degrade the security of these protocols. Established results indicate that, perhaps surprisingly, maximal security is achieved when the network is as small as two nodes due to increased delays in larger networks. This contradicts the very foundation of blockchains, namely that decentralization improves security. In this paper, we take a closer look at how the network scale affects security of Nakamoto-style blockchains. We argue that a crucial aspect has been neglected in existing security models: the larger the network, the harder it is for an attacker to control a significant amount of power. To this end, we introduce a probabilistic corruption model to express the increasing difficulty for an attacker to corrupt resources in larger networks. Based on our model, we analyze the impact of the number of nodes on the (maximum) network delay and the fraction of adversarial power. In particular, we show that (1) increasing the number of nodes eventually violates security, but (2) relying on a small number of nodes does not provide decent security provisions either. We then validate our analysis by means of an empirical evaluation emulating hundreds of thousands of nodes in deployments such as Bitcoin, Monero, Cardano, and Ethereum Classic. Based on our empirical analysis, we concretely analyze the impact of various real-world parameters and configurations on the consistency bounds in existing deployments and on the adversarial power that can be tolerated while providing security. As far as we are aware, this is the first work that analytically and empirically explores the real-world tradeoffs achieved by current popular Nakamoto-style deployments.
In the rapidly evolving domain of the Internet of Things (IoT) and fog computing, maintaining security, scalability, and efficient operation poses significant challenges. Addressing these issues, this study introduces "BlockFog," a novel blockchain-based framework designed to bolster intrusion defense in IoT fog computing environments. The core objective of BlockFog is to counteract the vulnerabilities inherent in decentralized IoT ecosystems by leveraging blockchain technology for enhanced security and transparency. The framework's innovative design integrates crucial components such as Device Onboarding & Identity Management, Data Integrity & Logging, Smart Contract-Driven Intrusion Detection, Automated Blockchain Responses, Secure Peer-to-Peer Communication, and a Lightweight Consensus Mechanism. These elements work collectively to ensure the security and functionality of IoT devices within the fog computing paradigm. BlockFog stands out for its meticulous approach to handling high transaction volumes with off-chain computations and layer-2 solutions, ensuring data integrity and facilitating seamless audit processes. The framework's resilience is further demonstrated through its robust response to evolving cyber threats, incorporating Over-the-Air (OTA) updates and advanced data protection mechanisms like zero-knowledge proofs. A comparative analysis highlights BlockFog's superior performance against existing models. The results reveal BlockFog's lower latency rates in normal, high traffic, and attack scenarios, its higher throughput efficiency, and its more effective resource utilization in terms of CPU, memory, and bandwidth usage. Moreover, BlockFog exhibits an enhanced ability to detect and respond to malicious activities, including DDoS attacks, with significantly higher accuracy than its counterparts. These findings underscore BlockFog's potential in redefining security and operational paradigms in IoT fog computing, making it a robust, agile, and transparent framework suitable for the current digital landscape.
Yang Liu, Song Peng, Miaomiao Zhang, Shidong Shi · 5 authors
The future of communication systems is undergoing a transformative shift towards intelligence, efficiency, and flexibility. Presently, the amalgamation of blockchain technology and the sixth-generation mobile communication network (6G) has garnered significant attention, as their fusion is poised to profoundly impact the digital economy and society at large. However, the convergence of blockchain and 6G networks poses challenges pertaining to security and performance. In this article, we propose an approach based on the design of secure mechanisms and performance optimization to delve into the key issues surrounding the integration of blockchain and 6G networks from both security and performance perspectives. Specifically, we first introduce the application scenarios of 6G networks and blockchain's empowerment of them to highlight the necessity of combining blockchain technology with 6G. Subsequently, in order to ensure the security of communication and data transmission between blockchain and 6G networks, we have investigated the design requirements for security mechanisms. Furthermore, we discuss the efficient realization of the amalgamation between blockchain and 6G networks by proposing a solution based on Directed Acyclic Graph (DAG) for blockchain's asynchronous consensus protocol, alongside optimization strategies for storage and communication to meet the desired characteristics and requirements of 6G networks. Lastly, we provide valuable research directions that serve as references and guidance for the future development of the integration between blockchain and 6G networks.
Burhan Ul Islam Khan, Khang Wen Goh, Mohammad Shuaib Mir, Nur Fatin Liyana Mohd Rosely · 6 authors
As the Internet of Things (IoT) continues to revolutionize value-added services, its conventional architecture exhibits persistent scalability and security vulnerabilities, jeopardizing the trustworthiness of IoT-based services. These architectural limitations hinder the IoT’s Sensor-as-a-Service (SEaaS) model, which enables the commercial transmission of sensed data through cloud platforms. This study proposes an innovative computational framework that integrates decentralized blockchain technology into the IoT architectural design, specifically enhancing SEaaS efficiency. This research contributes to an optimized IoT architecture with decentralized blockchain operations and simplified public key encryption. Furthermore, this study introduces an advanced SEaaS model featuring innovative trading operations for sensed data among diverse stakeholders. At its core, this model presents a unique blockchain-based data-sharing mechanism that manages multiple aspects, from enrollment to validation. Evaluations conducted in a standard Python environment indicate that the proposed SEaaS model outperforms existing blockchain-based data-sharing models, demonstrating approximately 40% less energy consumption, 18% increased throughput, 16% reduced latency, and a 25% reduction in algorithm processing time. Ultimately, integrating a lightweight authentication mechanism using simplified public key cryptography within the blockchain establishes the model’s potential for efficient and secure data-sharing in IoT.