The energy-intensive characteristics of the computations performed by graphics processing units (GPUs) in proof-of-work (PoW) blockchain technology are readily apparent. The optimization of GPU feature configuration is a complex subject that significantly impacts a systemâs energy consumption and performance efficiency. The primary objectives of this study are to examine and improve the energy consumption characteristics of GPUs, which play a crucial role in the functioning of blockchains and the mining of cryptocurrencies. This study examines the complex relationship between GPU configurations and system architecture components and their effects on energy efficiency and sustainability. The methodology of this study conducts experiments involving various GPU models and mining software, evaluating their effectiveness across various configurations and environments. Multilinear regression analysis is used to study the complex relationships between critical performance indicators like power consumption, thermal dynamics, core speed, and hash rate and their effects on energy efficiency and performance. The results reveal that strategically adjusting GPU hardware, software, and configuration can preserve substantial energy while preserving computational efficiency. GPU core speed, temperature, core memory speed, ETASH algorithms, fan speed, and energy usage significantly affected the dependent computational-efficiency variable (p = 0.000 and R2 = 0.962) using multilinear regression analysis. GPU core speed, temperature, core memory speed, fan speed, and energy usage significantly affected efficient energy usage (p = 0.000 and R2 = 0.989). The contributions of this study offer practical recommendations for optimizing the feature configurations of GPUs to reduce energy consumption, mitigate the environmental impacts of blockchain operations, and contribute to the current research on performance in PoW blockchain applications.
Yash Bobde, Gokuleshwaran Narayanan, Manas Jati, S. P. Raja · 6 authors
In the rapidly evolving landscape of industrial ecosystems, Industrial IoT networks face increasing security challenges. Traditional security methods often struggle to protect these networks adequately, posing risks to data integrity, confidentiality, and access control. Our research introduces a methodology that leverages blockchain technology to enhance the security and trustworthiness of IoT networks. This approach starts with sensor nodes collecting and compressing data, followed by encryption using the ChaCha20-Poly1305 algorithm and transmission to local aggregators. A crucial element of our system is the private blockchain gateway, which processes and classifies data based on confidentiality levels, determining their storage in cloud servers or the Interplanetary File System for enhanced security. The systemâs integrity and authenticity are further reinforced through the proof of authority consensus mechanism. This system employs Zero Knowledge Proof challenges for device authorization, optimizing data retrieval while maintaining a delicate balance between security and accessibility. Our methodology contributes to mitigating vulnerabilities in Industrial IoT networks and is part of a broader effort to advance the security and operational efficiency of these systems. It reflects an understanding of the diverse and evolving challenges in IoT security, emphasizing the need for continuous innovation and adaptation in this dynamic field.
This article presents a secure framework for remote healthcare monitoring in the context of home isolation, thereby addressing the concerns related to untrustworthy client connections to a hospital information system (HIS) within a secure network. Our proposed solution leverages a public blockchain network as a secure distributed database to buffer and transmit patient vital signs. The framework integrates an algorithm for the secure gathering and transmission of vital signs to the Ethereum network. Additionally, we introduce a publish/subscribe paradigm, thus enhancing security using the TLS channel to connect to the blockchain network. An analysis of the maintenance cost of the distributed database underscores the cost-effectiveness of our approach. In conclusion, our framework provides a highly secure and economical solution for remote healthcare monitoring in home isolation scenarios.
Considering the privacy challenges of secure storage and controlled flow, there is an urgent need to realize a decentralized ecosystem of private blockchain for cyberspace. A collaboration dilemma arises when the participants are self-interested and lack feedback of complete information. Traditional blockchains have similar faults, such as trustlessness, single-factor consensus, and heavily distributed ledger, preventing them from adapting to the heterogeneous and resource-constrained Internet of Things. In this paper, we develop the game-theoretic design of a two-sided rating with complete information feedback to stimulate collaborations for private blockchain. The design consists of an evolution strategy of the decision-making network and a computing power network for continuously verifiable proofs. We formulate the optimum rating and resource scheduling problems as two-stage iterative games between participants and leaders. We theoretically prove that the Stackelberg equilibrium exists and the group evolution is stable. Then, we propose a multi-stage evolution consensus with feedback on a block-accounting workload for metadata survival. To continuously validate a block, the metadata of the optimum rating, privacy, and proofs are extracted to store on a lightweight blockchain. Moreover, to increase resource utilization, surplus computing power is scheduled flexibly to enhance security by degrees. Finally, the evaluation results show the validity and efficiency of our model, thereby solving the collaboration dilemma in the private blockchain.
Currently, with the rapid development of smart home technology, the demand for establishing efficient and sustainable smart home systems in rural areas is increasing. However, in rural environments, the effective management and intelligent control of green energy face many challenges. To address these issues, this work aims to design a smart home system based on blockchain technology to achieve efficient energy management and intelligent control in a green lighting environment in rural areas. The main goals include improving the performance and safety of the system to meet the lighting needs of rural areas and promote sustainable development. The system comprises two primary components: the home gateway and cloud services. These components encompass functions like data monitoring and transmission, cloud storage, and remote control. The work also introduces the structural interaction, user node interaction, and the data security transmission scheme of the smart home system. Ultimately, the system's effectiveness is confirmed through simulation experiments. The results demonstrate that the system achieves the lowest latency when the transaction arrival rate is 40tps and the block size is 10. Additionally, the access control scheme based on the Hyperledger Fabric consortium chain can efficiently handle access requests for smart home resources and meet the practical application requirements within an appropriate range of security parameters. The main research conclusion is that the designed smart home system based on blockchain technology has achieved significant results in improving performance and security. This not only provides reliable lighting solutions for rural areas, but also provides important theoretical and practical guidance for the future development of smart home systems. The direction of future work includes further optimizing system performance, expanding the scope of application, and exploring more advanced blockchain technology applications in the field of smart homes. This will provide more possibilities and innovative directions for the development of future smart home systems.
Kamanashis Biswas, Mohammad Jabed Morshed Chowdhury, Muhammad Usman
As Internet of Things (IoT) technologies become increasingly integrated into our daily lives through a multitude of Internet-enabled devices, the efficient, secure, and cost-effective management of the vast amount of data generated by these devices poses a significant challenge [...].
The Internet of Things (IoT) has revolutionized industries by enabling the interconnection of devices, creating opportunities for enhanced automation and real-time data analysis. However, the rapid proliferation of IoT devices has introduced significant security vulnerabilities, such as unauthorized access, data manipulation, and privacy breaches. These challenges stem from the inherent limitations of IoT devices, such as low computational power, and the reliance on centralized security models that are susceptible to single points of failure. To address these issues, this paper proposes a Blockchain-Based Secure Framework for IoT devices. Blockchain, a decentralized, immutable, and transparent distributed ledger technology, offers an effective solution for securing IoT networks. By leveraging blockchain's cryptographic features and consensus mechanisms, this framework ensures secure device authentication, data integrity, and transparent communication between IoT devices. Devices can securely authenticate themselves through blockchain-based digital identities, eliminating the need for centralized servers, thus reducing the risk of unauthorized access.Moreover, the framework guarantees data integrity by recording all IoT transactions on the blockchain, making them tamper-proof and verifiable. Blockchain's decentralized nature also mitigates the risk of Distributed Denial of Service (DDoS) attacks by removing central points of vulnerability. Privacy is enhanced through techniques such as zero-knowledge proofs, allowing users to control access to their personal data. This proposed framework not only enhances IoT security but also provides scalability, transparency, and resilience. By combining the strengths of blockchain with IoT, it offers a robust solution for secure, reliable, and privacy-preserving communication in the ever-growing IoT ecosystem. The integration of blockchain technology is poised to transform IoT security, facilitating the secure deployment and management of IoT devices across various industries.
Venkata K. V. V. Bathalapalli, Saraju P. Mohanty, Elias Kougianos, Vasanth Iyer · 5 authors
This article presents a novel hardware-assisted distributed ledger-based solution for simultaneous device and data security in smart healthcare. This article presents a novel architecture that integrates PUF, blockchain, and Tangle for Security-by-Design (SbD) of healthcare cyber-physical systems (H-CPSs). Healthcare systems around the world have undergone massive technological transformation and have seen growing adoption with the advancement of Internet-of-Medical Things (IoMT). The technological transformation of healthcare systems to telemedicine, e-health, connected health, and remote health is being made possible with the sophisticated integration of IoMT with machine learning, big data, artificial intelligence (AI), and other technologies. As healthcare systems are becoming more accessible and advanced, security and privacy have become pivotal for the smooth integration and functioning of various systems in H-CPSs. In this work, we present a novel approach that integrates PUF with IOTA Tangle and blockchain and works by storing the PUF keys of a patient's Body Area Network (BAN) inside blockchain to access, store, and share globally. Each patient has a network of smart wearables and a gateway to obtain the physiological sensor data securely. To facilitate communication among various stakeholders in healthcare systems, IOTA Tangle's Masked Authentication Messaging (MAM) communication protocol has been used, which securely enables patients to communicate, share, and store data on Tangle. The MAM channel works in the restricted mode in the proposed architecture, which can be accessed using the patient's gateway PUF key. Furthermore, the successful verification of PUF enables patients to securely send and share physiological sensor data from various wearable and implantable medical devices embedded with PUF. Finally, healthcare system entities like physicians, hospital admin networks, and remote monitoring systems can securely establish communication with patients using MAM and retrieve the patient's BAN PUF keys from the blockchain securely. Our experimental analysis shows that the proposed approach successfully integrates three security primitives, PUF, blockchain, and Tangle, providing decentralized access control and security in H-CPS with minimal energy requirements, data storage, and response time.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Physical Unclonable Functions (PUFs) and Hardware Security
Bitcoin Core serves as the foundational software responsible for verifying and validating all transactions and blocks within the Bitcoin blockchain, hence upholding the security and integrity of the whole Bitcoin network. This study extensively examines the internal mechanisms, structure, and conceptual framework of Bitcoin Core. This study aims to conduct a comprehensive analysis of the Bitcoin Core architecture, with a focus on evaluating its capacity to fulfill the rigorous demands of a decentralized Bitcoin network. This study not only provides a comprehensive understanding of the essential elements that drive the Bitcoin network, but it also explores the numerous factors that have a substantial impact on the operational availability of Bitcoin nodes. All of these factors are essential for ensuring the efficient operation of the Bitcoin network, encompassing the physical environment, architectural designs of nodes, and maintenance requirements. This study provides a comprehensive analysis of the underlying mechanisms of Bitcoin, shedding light on its inherent robustness and the factors that contribute to its consistent performance within the ever-changing landscape of digital currencies. The objective of this endeavor is to furnish a detailed exposition of the mechanics of Bitcoin, so enhancing its prevalence and familiarity among individuals.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
Recently, blockchain-based IoT solutions have been proposed that address trust limitation by maintaining data consistency, immutability, and chronology in IoT environments. However, IoT ecosystems are resource-constrained and have low bandwidth and finite computing power of sensor nodes. Thus, the inclusion of blockchain requires an effective policy design regarding consensus and smart contract environments in heterogeneous IoT applications. Recent studies have presented blockchain as a potential solution in IoT, but an effective view of consensus and smart contract design to meet the end application requirements is an open problem. Motivated by the same, the survey presents the integration of suitable low-powered consensus protocols and smart contract design to assess and validate the blockchain-IoT ecosystems. We discuss the key blockchain concepts and present the scalability and performance issues of consensus protocols to support IoT. Further, we discuss smart contract vulnerabilities and blockchain attacks. Open issues and future directions are presented, supported through a case study of low-powered consensus protocol design in the blockchain- IoT ecosystem. The survey intends to drive novel solutions for future consensus and safe, smart contract designs to support applicative IoT ecosyst
In todayâs digital landscape, the exponential growth of data heightens security risks associated with traditional centralized storage systems. Utilizing blockchain technology, a shift towards decentralized data storage provides a more secure and private alternative. Central to our work is the exploration of symmetry in data management, a concept woven into the fabric of our proposed solution to challenge the inherency in InterPlanetary File System (IPFS) technology. Through the strategic utilization of smart contract-invoked random functions, our blockchain-based solution fragments and securely stores data in order to ensure a symmetrical balance between confidentiality and integrity. Our research endeavors are to contribute a robust, ethically grounded data storage framework fostering advancements in secure data sharing. The implications of this paper are significant in addressing contemporary challenges of data management within the expansive realm of big data.
Fog computing, a paradigm that extends cloud computing closer to the edge of the network, has emerged as a transformative solution to address the growing demands of latency-sensitive applications and the massive influx of data from the Internet of Things (IoT). Unlike traditional cloud computing, which centralizes data processing and storage in distant data centers, fog computing leverages a distributed architecture, bringing computation, storage, and networking resources closer to the end-users and devices. This abstract explores the key concepts, principles, and advantages of fog computing. By distributing computing resources across a continuum from the cloud to the edge, fog computing minimizes latency, enhances efficiency, and optimizes network bandwidth. The seamless integration of edge devices into the computing infrastructure facilitates real-time processing of data, enabling timely decision-making and improved user experiences in applications ranging from autonomous vehicles to smart cities. Furthermore, the abstract delves into the architectural components of fog computing, including fog nodes, gateways, and the interaction with cloud resources. The dynamic nature of fog environments allows for scalable and flexible deployments, catering to the diverse requirements of modern applications. Security and privacy concerns are also addressed, emphasizing the need for robust mechanisms to protect data integrity and user confidentiality in decentralized computing environments. As the digital landscape continues to evolve, fog computing emerges as a pivotal enabler of edge intelligence, empowering organizations to harness the benefits of real-time data processing and analysis at the edge of the network. The adoption of fog computing signifies a paradigm shift in the way we approach data management and processing, opening new avenues for innovation and efficiency in the era of the Internet of Things. Keywords: IOT, Fog Computing, Autonomous Vehicles.
Small and medium enterprises (SMEs) contribute to strengthening the global market by creating new jobs. Interactions among these companies may indeed be facilitated via e-commerce platforms. However, e-commerce activities seem to be a virtual face-to-face transactions, highly digital, and mutable. E-commerce based SMEs are frequently exposed to virtuous risks and competitive intensity. Blockchain is a digital database with the features of truthfulness, assurance, accountability, and intractability. It is made up of decentralized data storage, a consensus algorithm, and smart contracts. As a result, integrating e-commerce platforms and blockchain networks to help SMEs overcome their security difficulties. Conventional e-commerce platforms and storage depends on authorized intermediary networks or distributed cloud storage. Still, the failure of a single device is a danger, and third parties access, and data storage systems might be subject to data theft attacks. This paper presents a proof-of-authority (PoA) based consensus mechanism for e-commerce platforms in SMEs to address security issues in the network. This manuscript initially developed an energy-efficient PoA based consensus mechanism supported by e-commerce platforms for SMEs. We construct a comprehensive PoA consensus model based on pseudorandom number generator (PRNG) and accumulated validators number (AVN) for adding a new block in the conceptual framework. Finally, we demonstrate the security performance of the proposed consensus mechanism to help SMEs solve finance and trading issues. To evaluate the energy performance of the proposed model, we did a CPU utilization analysis and compared it with existing consensus protocols.
Parwinder Singh, Michail J. Beliatis, Mirko Presser
Dataspace and emerging technologies play a key role in developing value chain systems using cross-domain data, services and systems integration. Therefore, this study has conducted a comprehensive literature review for six years (2017-2022) on the convergence of Internet of Things (IoT), Artificial Intelligence (AI) and Distributed Ledger (Blockchain) technologies for supporting Dataspace integration efforts at the Edge. As an outcome, this study has identified relevant challenges that include heterogeneity, integration and interoperability, distributed security, trust, scalability, and resource management. It has also been found that very limited research covers the architectural aspects of distributed edge in the context of the convergence of technologies for Dataspace integration purposes. Therefore, this study has proposed an architectural framework - Distributed Edge Network Operations-oriented Semantic (DENOS) model that extends the traditional Cloud-Edge-Device architecture with three new layers - Semantic, Convergence, and Dataspace integration. In addition, the model leverages the power of semantic modelling (i.e., Processing, Service, and Data) context, which enables the model to have a dynamic implementation context to suit the diverse needs of target use cases. To showcase the validation of the model, a use case related to the digital traceable operation of the wind energy domain has been presented. The objective of the DENOS model is to enable Dataspace integration to build edge-enabled value chain networks. Thus, it contributes to secure and semantic integration using the convergence of resources and technologies, cross-domain collaboration, reusability and data-driven decision-making of resources.
Abstract The most important and difficult challenge the digital society has recently faced is ensuring data privacy and security in cloudâbased Internet of Things (IoT) technologies. As a result, many researchers believe that the blockchain's Distributed Ledger Technology (DLT) is a good choice for various clever applications. Nevertheless, it encountered constraints and difficulties with elevated computing expenses, temporal demands, operational intricacy, and diminished security. Therefore, the proposed work aims to develop a Decentralized Identifiable Distributed Ledger TechnologyâBlockchain (DIDLTâBC) framework that is intelligent and effective, requiring the least amount of computing complexity to ensure cloud IoT system safety. In this case, the Rabin algorithm produces the digital signature needed to start the transaction. The public and private keys are then created to verify the transactions. The block is then built using the DIDLT model, which includes the block header information, hash code, timestamp, nonce message, and transaction list. The primary purpose of the Blockchain Consent Algorithm (BCA) is to find solutions for numerous unreliable nodes with varying hash values. The novel contribution of this work is to incorporate the operations of Rabin digital data signature generation, DIDLTâbased blockchain construction, and BCA algorithms for ensuring overall data security in IoT networks. With proper digital signature generation, key generation, blockchain construction and validation operations, secured data storage and retrieval are enabled in the cloudâIoT systems. By using this integrated DIDLTâBCA model, the security performance of the proposed system is greatly improved with 98% security, less execution time of up to 150 ms, and reduced mining time of up to 0.98 s.
Ehtisham Ul Haque, Adil Shah, Jawaid Iqbal, Syed Sajid Ullah · 6 authors
Abstract Recent research has focused on applying blockchain technology to solve security-related problems in Internet of Things (IoT) networks. However, the inherent scalability issues of blockchain technology become apparent in the presence of a vast number of IoT devices and the substantial data generated by these networks. Therefore, in this paper, we use a lightweight consensus algorithm to cater to these problems. We propose a scalable blockchain-based framework for managing IoT data, catering to a large number of devices. This framework utilizes the Delegated Proof of Stake (DPoS) consensus algorithm to ensure enhanced performance and efficiency in resource-constrained IoT networks. DPoS being a lightweight consensus algorithm leverages a selected number of elected delegates to validate and confirm transactions, thus mitigating the performance and efficiency degradation in the blockchain-based IoT networks. In this paper, we implemented an Interplanetary File System (IPFS) for distributed storage, and Docker to evaluate the networkâs performance in terms of throughput, latency, and resource utilization. We divided our analysis into four parts: Latency, throughput, resource utilization, and file upload time and speed in distributed storage evaluation. Our empirical findings demonstrate that our framework exhibits low latency, measuring less than 0.976 milliseconds. The proposed technique outperforms Proof of Stake (PoS), representing a state-of-the-art consensus technique. We also demonstrate that the proposed approach is useful in IoT applications where low latency or resource efficiency is required.
Muhammad Faheem, Heidi Kuusniemi, Bahaa Eltahawy, Muhammad Shoaib Bhutta · 5 authors
Abstract Energy is a crucial need in today's world for powering homes, businesses, transportation, and industrial processes. Fossil fuels, such as oil, coal, and natural gas, have been the primary sources of energy for decades. However, there is growing recognition of the negative environmental impact of fossil fuels and the need to transition to cleaner and more sustainable sources of energy. Distributed Energy Resources , such as wind and solar offer several benefits including, reducing energy costs, increasing resiliency, and decreasing carbon emissions. However, the integration of () into the grid requires advanced communication and secure control strategies to ensure a stable and reliable grid operations. In this regard, a blockchainâbased industrial wireless sensor network can provide secure and resilience data transmission to facilitate intelligent integration, monitoring, and control of in the smart grid. In this research, a smart contracts framework in Solana called Advanced Solana Blockchain () is proposed for in the smart grid. The proposed scheme enables resilient and secure realâtime control and monitoring of in smart grids. The performance evaluations and security analysis illustrated that this scheme is secure, reliable, and suitable in terms of lightweight data sharing between in smart grids.
With the rapid development of artificial intelligence (AI) in the healthcare industry, the sharing of personal healthcare data plays an essential role in advancing medical AI. Unfortunately, personal healthcare data sharing is plagued by challenges like ambiguous data ownership and privacy leakage. Blockchain, which stores the hash of shared data on-chain and ciphertext off-chain, is treated as a promising approach to address the above issues. However, this approach lacks a flexible and reliable mechanism for incremental updates of the same case data. To avoid the overhead of authentication, access control, and rewards caused by on-chain data changes, we propose a blockchain and trusted execution environment (TEE)-based privacy-preserving sharing scheme for healthcare data that supports incremental updates. Based on chameleon hash and TEE, the scheme achieves reliable incremental updates and verification without changing the on-chain data. In the scheme, for privacy concerns, off-chain data are protected through symmetric encryption, whereas data verification, decryption, and computation are performed within TEE. The experimental results show the feasibility and effectiveness of the proposed scheme.
As the e-commerce industry continues to grow, the challenges around warranty issuing and its management have become more significant. This research paper presents a software implementation of a blockchain-based e-commerce warranty system that utilizes non-fungible tokens (NFTs) to simplify the warranty management process for both consumers and manufacturers. Its features include automatic warranty issuing, verification, transfer of ownership, and warranty expiration. The system was made available as a service and was integrated into an existing e-commerce website clone to evaluate the ease of use. Additionally, a page listing all warranty NFTs owned by a user, irrespective of the e-commerce site of purchase, was created and linked to the original e-commerce website. As a result, the implemented system simplified the manufacturer/sellerâs overhead of issuing and managing warranties and improved the user experience for consumers by showing all warranties owned by them in one place. This study illustrates the potential of public blockchains in the e-commerce sector, which has important implications for the use of blockchain-based warranty management systems. Received: 15 November 2023 | Revised: 26 December 2023 | Accepted: 3 January 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study.
In this paper, we propose hybrid consensus algorithms that combine machine learning (ML) techniques to address the challenges and vulnerabilities in blockchain networks. Consensus Protocols make ensuring agreement among the applicants in the distributed systems difficult. However, existing mechanisms are more vulnerable to cyber-attacks. Previous studies extensively explore the influence of cyber attacks and highlight the necessity for effective preventive measures. This research presents the integration of ML techniques with the proposed hybrid consensus algorithms and advantages over predicting cyber-attacks, anomaly detection, and feature extraction. Our hybrid approaches leverage and optimize the proposed consensus protocols' security, trust, and robustness. However, this research also explores the various ML techniques with hybrid consensus algorithms, such as Delegated Proof of Stake Work (DPoSW), Proof of Stake and Work (PoSW), Proof of CASBFT (PoCASBFT), Delegated Byzantine Proof of Stake (DBPoS) for security enhancement and intelligent decision making in consensus protocols. Here, we also demonstrate the effectiveness of the proposed methodology within the decentralized networks using the ProximaX blockchain platform. This study shows that the proposed research framework is an energy-efficient mechanism that maintains security and adapts to dynamic conditions. It also integrates privacy-enhancing features, robust consensus mechanisms, and ML approaches to detect and prevent security threats. Furthermore, the practical implementation of these ML-based hybrid consensus models faces significant challenges, such as scalability, latency, throughput, resource requirements, and potential adversarial attacks. These challenges must be addressed to ensure the successful implementation of the blockchain network for real-world scenarios.
The Internet of Things (IoT) is a technology that can connect billions of devices or âthingsâ to other devices (machine to machine) or even to people via an existing infrastructure. IoT applications in real-world scenarios include smart cities, smart houses, connected appliances, shipping, monitoring, smart supply chain management, and smart grids. As the number of devices all over the world is increasing (in all aspects of daily life), huge amounts of data are being produced as a result. New issues are therefore arising from the use and development of current technologies, regarding new applications, regulation, cloud computing, security, and privacy. The blockchain has shown promise in terms of securing and preserving the privacy of users and data, in a decentralized manner. In particular, Hyperledger Fabric v2.x is a new generation of blockchain that is open source and offers versatility, modularity, and performance. In this paper, a blockchain as a service (BaaS) application based on Hyperledger Fabric is presented to address the security and privacy challenges associated with the IoT. A new architecture is introduced to enable this integration, and is developed and deployed, and its performance is analyzed in real-world scenarios. We also propose a new data structure with encryption based on public and private keys for enhanced security and privacy.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
The use of blockchains in the Internet of Things is extremely promising, as it gives connected things the possibility to send and receive payments or tamper-proof data. In the last years, FlyClient has emerged in the literature as a technique for allowing resource constrained devices to verify blockchain transactions. FlyClient is based on Merkle Mountain Ranges (MMRs) and probabilistic sampling, and it allows us to develop blockchain clients whose resource consumption is sublinear with the length of the chain. However, this comes at the cost of a change in the blockchain format, which leads to forks that are politically expensive, because they require 51% consensus. In this paper we explore the possibility of fork-free FlyClient verification methods that leverage smart contract programming. Smart contracts are able to add functionalities to a blockchain without needing forks. This raises several and novel technical issues that we address in the paper. We show that fork-free sublinear clients are feasible without trusting the nodes that invoke the smart contract methods, as long as the smart contract language provides a means to access the most recent block or its hash. As a proof of concept we propose SmartFly, a fork-free FlyClient verification system for the Ethereum Classic blockchain. We measure several performance metrics of SmartFly, proving that it is succinct in storage and bandwidth consumption and economically bearable (about 38 euros per day to maintain the whole system).
In the modern digital landscape of the Internet of Things (IoT), data interoperability and heterogeneity present critical challenges, particularly with the increasing complexity of IoT systems and networks. Addressing these challenges, while ensuring data security and user trust, is pivotal. This paper proposes a novel Semantic IoT Middleware (SIM) for healthcare. The architecture of this middleware comprises the following main processes: data generation, semantic annotation, security encryption, and semantic operations. The data generation module facilitates seamless data and event sourcing, while the Semantic Annotation Component assigns structured vocabulary for uniformity. SIM adopts blockchain technology to provide enhanced data security, and its layered approach ensures robust interoperability and intuitive user-centric operations for IoT systems. The security encryption module offers data protection, and the semantic operations module underpins data processing and integration. A distinctive feature of this middleware is its proficiency in service integration, leveraging semantic descriptions augmented by user feedback. Additionally, SIM integrates artificial intelligence (AI) feedback mechanisms to continuously refine and optimise the middlewareâs operational efficiency.