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The adoption of blockchain platforms to bolster the security of Internet of Things (IoT) systems has attracted significant attention in recent years. Currently, there is a lack of comprehensive and systematic survey papers in the literature addressing these platforms. This paper discusses six of the most popular emerging blockchain platforms adopted by IoT systems and analyses their usage in state-of-the-art works to solve security problems. The platform was compared in terms of security features and other requirements. Findings from the study reveal that most blockchain components contribute directly or indirectly to IoT security. Blockchain platform components such as cryptography, consensus mechanism, and hashing are common ways that security is achieved in all blockchain platform for IoT. Technologies like Interplanetary File System (IPFS) and Transport Layer Security (TLS) can further enhance data and communication security when used alongside blockchain. To enhance the applicability of blockchain in resource-constrained IoT environments, future research should focus on refining cryptographic algorithms and consensus mechanisms to optimise performance and security. [ABSTRACT FROM AUTHOR]

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 network 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 ms. 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. [ABSTRACT FROM AUTHOR]

This work introduces a blockchain-based secure medical prescription-management system seamlessly integrated with a dynamic Internet of Things (IoT) framework. Notably, this integration constitutes a pivotal challenge in the arena of resource-constrained IoT devices: energy consumption. The choice of a suitable blockchain consensus mechanism emerges as the linchpin in surmounting this hurdle. Thus, this paper conducts a comprehensive comparison of energy consumption between two distinct consensus mechanisms: Proof of Work (PoW) and Quorum-based Byzantine fault tolerance (QBFT). Furthermore, an assessment of the most energy-efficient algorithm is performed across multiple networks and various parameters. This approach ensures the acquisition of reliable and statistically significant data, enabling meaningful conclusions to be drawn about the system's performance in real-world scenarios. The experimental results show that, compared to the PoW, the QBFT consensus mechanism reduced the energy consumption by an average of 5%. This finding underscores the significant advantage of QBFT in addressing the energy consumption challenges posed by resource-constrained IoT devices. In addition to its inherent benefits of privacy and block time efficiency, the Quorum blockchain emerges as a more sustainable choice for IoT applications due to its lower power consumption. [ABSTRACT FROM AUTHOR]

With the proposal of the concept of ubiquitous power Internet of Things and the further promotion of blockchain strategy, modern information technologies such as the Internet of Things and cloud computing have been widely used in the power system. While the power grid is becoming more intelligent, it is also accompanied by the emergence of various security threats, and the power grid will face greater challenges and pressures. In this paper, aiming at the current situation of information security faced by the power grid blockchain under the cloud Internet of Things, a multi-authorization center ciphertext policy attribute encryption access control method is constructed for the power grid blockchain. It adds the function of visitor attribute update revocation, aggregates multi-dimensional data into ciphertext, and uses CP-ABE encryption to implement fine-grained access control at the dimension level. Through experimental analysis, in terms of security and functionality, this method can resist physical collision attacks and manage access rights flexibly. In terms of encryption and decryption efficiency, the encryption and decryption calculation speed of the proposed method is 6.2–15.6% higher than that of the traditional method, and the time consumption efficiency is more than 5% higher than that of other methods. It proves that this model has more advantages for open network environments such as power grid blockchain with high confidentiality requirements and large scale of users. It is of great significance to study the data security and privacy protection methods of the power grid blockchain. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) refers to the network of interconnected devices that can communicate and share data over the Internet. The widespread adoption of smart devices within Internet of Things (IoT) networks poses considerable security challenges for their communication. To address these issues, blockchain technology, known for its decentralized and distributed nature, offers potential solutions within consensus-based authentication in IoT networks. This paper presents a novel approach called the local and global layer blockchain model, which aims to enhance security while simplifying implementation. The model leverages the concept of clustering to establish a local-global architecture, with cluster heads assuming responsibility for local authentication and authorization. Implementing a local private blockchain facilitates seamless communication between cluster heads and relevant base stations. This blockchain implementation enhances credibility assurance, strengthens security, and provides an effective network authentication mechanism. Simulation results indicate that the proposed algorithm outperforms previously reported methods. The proposed model achieved an average coverage per node of 0.9, which is superior to baseline models. Additionally, the lightweight blockchain model proposed in this paper demonstrates superior capabilities in achieving balanced network latency and throughput compared to traditional global blockchain approaches. [ABSTRACT FROM AUTHOR]

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Proof-of-Work (PoW) was the first blockchain consensus protocol discovered, followed by Proof-of-Stake and others. The disadvantage of the PoW is that it requires high energy consumption compared to other consensus protocols. Based on this weakness, some researchers proposed a lightweight blockchain technology, a modified blockchain that has a simplified algorithm but does not reduce the security factor. This lightweight blockchain is suitable for applications requiring data reliability but with limited computing resources, such as Internet of Things devices. This paper discussed and modified the SimBlock simulator as one of the existing blockchain simulators. It has a visualization tool to look further into the propagation transition of the block. Unfortunately, the existing PoW consensus on the SimBlock simulator is unable to pinpoint the actual hash computation method. Therefore, the hashing process in the SimBlock simulator was modified by including the difficulty level for finding the hash target. The purpose of including the difficulty level was to determine how long it takes to create a block. By knowing the time needed, a recommendation could be obtained for the most suitable difficulty level for a lightweight blockchain and its implementation with IoT devices. There are two options of approaches to the difficulty level referred to in this paper; finding the number of zeros that appear sequentially and are in front of a hash value (leading zero) and finding the number of zeros that appear arbitrarily (count zero). For example, the first difficulty level on a leading-zero quest has the same meaning as searching for a leading zero, the second level of difficulty is the search for the two leading zeros, etc. The block generation time on a blockchain network using the PoW consensus highly depends on the difficulty level. Block generation time and resource utility have been analyzed and compared with other blockchain simulators and existing networks, such as Ethereum and Bitcoin. The modified SimBlock simulator was tested in this experiment using 100–600 nodes, with the expected result of creating 100–1000 blocks. Based on the experiments, creating a block using leading zeros as the hash target for the first to fourth difficulty levels took less than 1 s, whereas when using count zeros (zero-count) as the target hash, it took less than 1 s for the first to fifteenth difficulty levels. Using leading zeros took approximately 237.4 s at difficulty level 7, while count-zero took approximately 633.8 s at difficulty level 19. The experiment was not continued at the next difficulty level because it required a longer compilation time. With the modifications made, the creation of a block on a blockchain network using the PoW consensus can be clearly seen. The difficulty level added to the simulator can also provide information for determining the difficulty level to be implemented on the lightweight blockchain. [ABSTRACT FROM AUTHOR]

Blockchain (BC) technology has attracted a lot of interest due to its excellent security and privacy features as well as its immutability. While BC can address security and privacy challenges in IoT, it is often computationally expensive, suffers from limited scalability, and introduces bandwidth overheads and delays, making it unsuitable for IoT applications. This paper proposes a novel lightweight and scalable blockchain (LIGHT-SB) designed specifically for IoT environments. In a smart IoT ecosystem, low-resource devices benefit from a centralized manager that handles communication keys and manages requests. LIGHT-SB enhances decentralization while maintaining robust privacy and security through a hybrid consensus algorithm combining permissionless proof-of-capacity and permissioned Byzantine fault tolerance (PoC-PBFT). Secure message delivery is achieved using SHA-256 and RSA cryptographic techniques. IoT device authentication, communication, and storage are safeguarded within the network. Distributed throughput management is implemented to monitor and adjust BC usage, ensuring it remains efficient. Qualitative evaluations demonstrate that LIGHT-SB effectively mitigates several security threats. [ABSTRACT FROM AUTHOR]

The huge amount of data produced by the Internet of Things need to be validated and curated to be prepared for the selection of relevant data in order to prototype models, train them, and serve the model. On the other side, blockchains and open data are also important data sources that need to be integrated into the proposed integrative models. It is difficult to find a sufficiently versatile and agnostic architecture based on the main machine learning frameworks that facilitate model development and allow continuous training to continuously improve them from the data streams. The paper describes the conceptualization, implementation, and testing of a new architecture that proposes a use case agnostic processing chain. The proposed architecture is mainly built around the Apache Submarine, an unified Machine Learning platform that facilitates the training and deployment of algorithms. Here, Internet of Things data are collected and formatted at the edge level. They are then processed and validated at the fog level. On the other hand, open data and blockchain data via Blockchain Access Layer are directly processed at the cloud level. Finally, the data are preprocessed to feed scalable machine learning algorithms. [ABSTRACT FROM AUTHOR]

The rapid proliferation of smart devices in Internet of Things (IoT) networks has amplified the security challenges associated with device communications. To address these challenges in 5G-enabled IoT networks, this paper proposes a multi-level blockchain security architecture that simplifies implementation while bolstering network security. The architecture leverages an adaptive clustering approach based on Evolutionary Adaptive Swarm Intelligent Sparrow Search (EASISS) for efficient organization of heterogeneous IoT networks. Cluster heads (CH) are selected to manage local authentication and permissions, reducing overhead and latency by minimizing communication distances between CHs and IoT devices. To implement network changes such as node addition, relocation, and deletion, the Network Efficient Whale Optimization (NEWO) algorithm is employed. A localized private blockchain structure facilitates communication between CHs and base stations, providing an authentication mechanism that enhances security and trustworthiness. Simulation results demonstrate the effectiveness of the proposed clustering algorithm compared to existing methodologies. Overall, the lightweight blockchain approach presented in this study strikes a superior balance between network latency and throughput when compared to conventional global blockchain systems. Further analysis of system under test (SUT) behavior was accomplished by running many benchmark rounds at varying transaction sending speeds. Maximum, median, and lowest transaction delays and throughput were measured by generating 1000 transactions for each benchmark. Transactions per second (TPS) rates varied between 20 and 500. Maximum delay rose when throughput reached 100 TPS, while minimum latency maintained a value below 1 s. [ABSTRACT FROM AUTHOR]

Summary: Sharing trusted data among trusted stakeholders is very important to large‐scale Internet of Things (IoT) applications. However, the entities and organizations involved in IoT naturally lack trusted relationships, which poses significant challenges to the above vision. Specifically, the first challenge is to ensure that the data in the physical world can be objectively and truly injected into the information world of IoT. The second is to ensure the credibility of the entities' identities in IoT. The third is to ensure the authenticity of data, the credibility of identity, and the reliable transmission of data when a third trusted party is unable to provide the expected trusted services. In view of the above challenges, this paper proposes a secure and lightweight triple‐trusting architecture (SLTA), which fully uses a blockchain‐related supporting technology. The architecture includes an oracle‐based data collection mechanism, which ensures that the data collected from edge devices of IoT cannot be modified, and the distributed identity management mechanism, which enhances personal privacy, security, and control of digital identities. Furthermore, a series of innovative designs for applying the blockchain to special large‐scale cooperation scenario in IoT are proposed, which is also a part of the key mechanisms of the SLTA. The innovative design includes a new software‐defined blockchain structure model and a lightweight Byzantine fault‐tolerant algorithm that provides credible support for decentralized data collection, identity management, and data transfer, as well as low‐overhead sequential storage mechanism. [ABSTRACT FROM AUTHOR]

Today, the manner in which we communicate has greatly advanced. The technology is not just about machines, but people with technology together. Machine-to-machine (M2M) communication is unavoidable in the Internet of things. However, at the same time, there are more attacks against the M2M system. Therefore, a reliable and secure authentication mechanism is required. Blockchain technology is decentralized and highly secure while being tamper-proof. This protects M2M service providers by eliminating the single point of failures. This paper proposes a blockchain-based authentication scheme that uses a practical Byzantine fault tolerance (pBFT) consensus mechanism for M2M security in cyber physical systems. By implementing a blockchain to an M2M system, it provides an ID for devices on the blockchain. Simulation results have shown that the data on the chain cannot be altered. A pBFT consensus algorithm also ensures that the blockchain network is able to come to a consensus with faults. [ABSTRACT FROM AUTHOR]

Security in Internet of Things (IoT) remains a significant concern within academia and industry. With the great potential of IoT data, the traditional centralized architecture of IoT system is limited and cannot afford security solutions. In this paper, to address the issue of IoT data security, we propose a blockchain-based data acquisition and processing architecture. The proposed architecture ensures IoT data security through data consistency. It supports distributed IoT nodes to negotiate consensus on the processed data, and decides to write the consensus data to blockchain ledger. Since distributed nodes are non-peer and have different voting weights in the proposed architecture, traditional consensus algorithms are not applicable. Therefore, we design a novel consensus algorithm for data consistency between non-peer nodes: Byzantine Fault-Tolerant consensus algorithm based on Dynamic Permission Adjustment (DPA-PBFT) algorithm. The DPA-PBFT algorithm works in the consensus domain of different weight nodes with the ability of self-optimize. It improves consensus efficiency and reduces communication overhead for data consistency. Finally, we conduct numerous experiments to evaluate the performance improvement of the DPA-PBFT algorithm under the proposed distributed architecture. [ABSTRACT FROM AUTHOR]

Sharing data across various Internet of Things (IoT) devices has been a common challenge due to efficiency, security, and stability issues. Blockchain, with security features, is considered to be a potential solution for data sharing in IoT settings. However, traditional blockchain-based solutions cannot satisfy the efficiency requirement of high-frequency data sharing among IoT devices. In this paper, we propose an efficient IoT data sharing approach by adopting the Payment Channel Network (PCN)-extended blockchain. Besides, we develop a homomorphic hashing-based transaction segmentation scheme to solve the issue of low transaction success ratio caused by channel deposit restrictions in PCN. In addition, a Multi-point Relay (MPR)-based multi-path routing scheme has been developed to ensure high-frequency transaction forwarding. The communication overhead of maintaining the routing table is reduced by our proposed Multi-point Relay Selection algorithm, and multiple alternate paths generated by Multiple Routing Path algorithm can improve the transaction success rate. Experiment evaluations have demonstrated that that our proposed approach outperforms the baseline approaches in terms of the transaction efficiency and success ratio. [ABSTRACT FROM AUTHOR]

In modern scenarios, Industry 4.0 entails invention with various advanced technology, and blockchain is one among them. Blockchains are incorporated to enhance privacy, data transparency aswell as security for both large and small scale enterprises. Industry 4.0 is considered as a new synthesis fabrication technique that permits the manufacturers to attain their target effectively. However, because numerous devices and machines are involved, data security and privacy are always concerns. To achieve intelligence in Industry 4.0, blockchain technologies can overcome potential cybersecurity constraints. Nowadays, the blockchain and internet of things (IoT) are gaining more attention because of their favorable outcome in several applications. Though they generate massive data that need to be effectively optimized and in this research work, deep learning-based techniques are employed for this. This paper proposes a novel mutated leader sine cosine algorithm-based deep convolutional neural network (MLSC-DCNN) in order to attain a secure and optimized IoT blockchain for Industry 4.0. Here, an MLSC is hybridized using a mutated leader and sine cosine algorithm to enhance the weight function and minimize the loss factor of DCNN. Finally, the experimentation is carried out for various simulation measures. The comparative analysis is made for Best Tip Selection Method (BTSM), Smart Block-Software Defined Networking (SDN), and the proposed approach. The evaluation results show that the proposed approach attains better performances than BTSM and SDN. [ABSTRACT FROM AUTHOR]

The basic properties of blockchain, such as decentralization, security, and immutability, show promising potential for IoT applications. The main feature—decentralization of blockchain technology—depends on the consensus. However, consensus algorithms are mostly designed to work in extensive computational and communication environments for network security and immutability, which is not desirable for resource-restricted IoT applications. Many solutions are proposed to address this issue with modified consensus algorithms based on the legacy consensus, such as the PoW, PoS, and BFT, and new non-linear data structures, such as DAG. A systematic classification and analysis of various techniques in the field will be beneficial for both researchers and industrial practitioners. Most existing relevant surveys provide classifications intuitively based on the domain knowledge, which are infeasible to reveal the intrinsic and complicated relationships among the relevant basic concepts and techniques. In this paper, a powerful tool of systematic knowledge classification and explanation is introduced to structure the survey on blockchain consensus algorithms for resource-constrained IoT systems. More specifically, an ontology was developed for a consensus algorithm apropos of IoT adaptability. The developed ontology is subdivided into two parts—CONB and CONIoT—representing the classification of generic consensus algorithms and the ones that are particularly proposed for IoT, respectively. Guided by this ontology, an in depth discussion and analysis are provided on the major consensus algorithms and their IoT compliance based on design and implementation targets. Open research challenges and future research directions are provided. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) makes attractive services available to smart objects and humans. To aim this, IoT devices need high sensing, reasoning, and real-time acting capabilities that can be also obtained by promoting adaptive forms of cooperation machine-to-machine among smart objects. The convergence of IoT and multiagent systems also relies on the association between software agents with IoT devices for exploiting their social attitude of interacting and cooperating for services. However, the choice of reliable partners for cooperation can be very difficult when IoT devices migrate across different environments, where the most part of their members will be unreferenced with respect to their trustworthiness. It is well known that agents reputation can be a viable aspect to consider to form social groups; therefore, a possible solution to this problem is to form groups of agents in each IoT environment, based on their social capabilities. In this respect, the first contribution of this paper is represented by a reputation model focused on building the reputation capital of each agent. Second, an algorithm capable to form groups of agents in IoT environments on the basis of their reputation capital was designed. Finally, since in this contest, it is important to spread reliable and certified information about the device/agent reputation in a distributed environment, the third contribution is represented by the adoption of the blockchain technology to certify the reputation capital. Some experiments we have performed show that the model is capable to detect almost all the misleading agents if their percentage is under a high enough threshold, and that good results in term of group composition are obtained. Moreover, the simulations show that, by adopting our model, malicious devices always pay for services significantly more than honest ones. We argue that the individual reputation capital of devices and, consequently, the overall reputation capital of the IoT community can take benefit from the adoption of the proposed approach. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) suffers from a profound lack of trust between central gateways and sensors, e.g., gateways suspect sensors of flooding malicious packets, and vice versa, sensors suspect gateways of manipulating traffic data. One important reason for the mistrust is the asymmetry of a centralized network organization. A Decentralized Autonomous Organization (DAO) can establish a trustful and symmetric network with the blockchain. However, it is a vacant area for IoT networks to build trust between gateways and sensors within the DAO. In this paper, we firstly propose a trustful and secure IoT Network DAO solution (NetDAO) to mitigate the data manipulation and the malicious flooding packets. In particular, the NetDAO has a security rating algorithm to assign a reputation value for each entity in the network. Based on this, each entity can mitigate the malicious flooding packets using a proof-of-reputation packet-forwarding mechanism. In addition, the NetDAO stores traffic data using the blockchain to mitigate the data manipulation. The experimental results show that the NetDAO effectively mitigates malicious flooding packets and costs 1 s for ∼480 entities to complete the rating algorithm. [ABSTRACT FROM AUTHOR]

Blockchain and IoT are two technologies are most widely popular in present scenario, but technologies are more complicated. The blockchain used to transforms storage and data analysis. In recent years, the blockchain is at the heart of computer technologies. It is a cryptographically secure distributed database technology for storing and transmitting information. Various attacks are done in many networks. Many research articles discussed about the security issues over the IoT based secure using block chain technology. In this paper, an Ensemble Integrated Security System (EISS) is introduced to improve the security for the heterogeneous network which consists of normal and abnormal nodes which is processed with the block chain, IoT. Results show the performance of the OUATH-2 and EISS algorithm. [ABSTRACT FROM AUTHOR]

Blockchain technology can solve the problems of centralized management and easy data loss in the traditional access control scheme of IoT to achieve distributed and high security access control, but it is easy to ignore the importance of establishing a dynamic and flexible access control mechanism such that the dynamic information of the network cannot be captured automatically when its node is damaged and its authorization policy is adjusted accordingly. This paper design an attribute-based access control mechanism for IoT with a trust and reputation system that assists authorization, and a multidimensional adaptation algorithm (MDAA) is proposed. Firstly, a public blockchain and a private sidechain are used to store sensitive information and public data separately, access threshold policies are defined by service consuming nodes register attributes and service providing nodes. Secondly, the trust and reputation system gradually quantifies the trust and reputation scores of each node in the network, when a service consumer node initiates an access request, the smart contract verifies whether the service consumer node satisfies thresholds of the attributes, trust and reputation required by the access threshold policy, the access privileges is available if satisfied. Finally, the trust and reputation scores of nodes are updated periodically based on interactions between nodes to achieve dynamic verification and authorization. Simulation results show that compared with TARAS algorithm and DADAC algorithm, MDAA supports two- way trust evaluation, has better algorithm convergence and reduces the delay in processing access control while ensuring authorization security, which is applicable. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is made up of intelligent devices that interact with each other. It allows information to be gathered and shared by these devices. In addition, IoT now has a wide range of life applications such as business, logistics, health monitoring, smart ecosystem, and information concerning individuals, social and private environments. Security-related issues involved in such a communication network are drastically increasing day by day. Therefore, existing authentication and authorization concepts must grow along with technological evolution. This paper presents an artificial intelligence (AI)-assisted Bio-inspired algorithm for secure IoT communication networks (AI-BIAS) to improve future communication. The proposed framework is categorized into two sections: First, the Bio-inspired algorithm-assisted blockchain technology for authentication and authorization in the IoT communication network is presented. Further, the Artificial Intelligence algorithm monitors the proposed IoT communication network. The experimental results show that the proposed model enhances the accuracy ratio of 98.3%, average latency of 26 ms, average cost of 25.7%, authentication time 0.04 ms, multistep prediction's MAPE, and RMSE values are 0.7645 and 0.9878 when compared to other popular methods. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has changed our lives significantly. Although IoT provides new opportunities, security remains a key concern while providing various services. Existing research methodologies try to solve the security and time-consuming problem also exists. To solve those problems, this paper proposed a Hashed Advanced Encryption Standard (HAES) algorithm based efficient key management system for internet-based lightweight devices in IoT networks. The proposed method is mainly divided into two phases namely Data Owner (DO) and Data User (DU) phase. The DO phase consists of two processes namely authentication and secure data uploading. In authentication, the registration process consists of three phases namely KGC, SCC and DVC. In Key Generation Center (KGC), the device ID is converted into a 128-bit hash key using the Point on Curve based Fowler–Noll–Vo (PoC-FNV) algorithm. In DVC, the Data Access Policy (DAP) is created by using the selected attributes which is in turn selected by using the Chen Chaotic Chimp Optimization Algorithm (CCCOA). Thus, the authentication information is stored in the blockchain. If the person is an authorized, then the data is securely stored and uploaded into the cloud server using HAES. In the DU phase, the DU sends the data access request to the blockchain then the blockchain forwards the request to the DO, if the DO accepts the request then the DU obtains the data by using the DAP. Finally, the performance of the proposed method is compared with the existing methods and attains better result than the existing research methodologies. [ABSTRACT FROM AUTHOR]

Internet of things is widely used in the current era to collect data from sensors and perform specific tasks through processing according to the requirements. The data collected can be sent to a blockchain network to create secure and tamper-resistant records of transactions. The combination of blockchain with IoT has huge potential as it can provide decentralized computation, storage, and exchange for IoT data. However, IoT applications require a low-latency consensus mechanism due to its constraints. In this paper, CBCIoT, a consensus algorithm for blockchain-based IoT applications, is proposed. The primary purpose of this algorithm is to improve scalability in terms of validation and verification rate. The algorithm is developed to be compatible with IoT devices where a slight delay is acceptable. The simulation results show the proposed algorithm's efficiency in terms of block generation time and transactions per second. [ABSTRACT FROM AUTHOR]

The smart city is a technological framework that connects the city's different components to create new opportunities. This connection is possible with the help of the Internet of Things (IoT), which provides a digital personality to physical objects. Some studies have proposed integrating Blockchain technology with IoT in different use cases as access, orchestration, or replicated storage layer. The majority of connected objects' capacity limitation makes the use of Blockchain inadequate due to its redundancy and its conventional processing-intensive consensus like PoW. This paper addresses these challenges by proposing a NOVEL model of a lightweight Blockchain framework (IoT-SmartChain), with a lightweight consensus and a lightweight structure. The framework architecture presents a role hierarchy of connected objects according to their computational and storage capacity. This organization allows all things to be linked even indirectly via different interfaces and to benefit from the power of high-capacity objects such as Fog and Edge computing nodes. Data is validated and added to the blockchain ledger by running a lightweight consensus called Proof of Random Participation (PoRP), which reduces the blockchain nodes' high computing power requirement. The TOPIC subscription-based data storage strategy called Assisted Selected Relevant Data in Local Ledger (ASRDLL) reduces the data size of a node's local ledger and the entire network's data size. This strategy is assisted by a centralized algorithm that optimizes the overall network size by adjusting the choice of TOPICS. The storage capacity, computational power, and energy consumption have been evaluated by a proof of concept implementation under NodeJS. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is helping the healthcare industry innovate. Medical professionals are no longer confined to hospitals or physical locations. IoT devices are used in healthcare for remote monitoring of vital signs, transmission and reception of private data, and other similar applications. Protection from cyber threats is the most vital aspect of IoT device operation. Malicious activities result in the leakage of sensitive data and the malfunctioning of devices, which becomes a critical issue. As a result, it is now a serious endeavor to create effective solutions that can safeguard the data and record exchange networks of every IoT device. To address some critical issues with current consensus algorithms, this paper proposes the verifiable random ranking (VRR) based Secure Blockchain Consensus (SBC) mechanism. In place of conventional algorithms, we developed new techniques for managing active nodes and evaluating node reliability and robustness. Our experiments show that the VRR-SBC algorithm speeds up consensus, improves security, and reduces the price of verification. The results of the simulation demonstrate the usefulness of the blockchain era for limited devices and provide an opportunity to assess the scope of the consensus algorithm's applicability. [ABSTRACT FROM AUTHOR]

Blockchain has revolutionized numerous fields, which include financial services, health care, the Internet of things, academia and supply chain management. Blockchain technology enables us to have an immutable, distributed ledger for managing the transactions of untrusted users. However, the technology has many open challenges, such as privacy leaks, scalability, and energy consumption. User identity can be easily tracked using network analysis, as transactions are accessible to everyone, which is a serious concern of blockchain. In this paper, we propose a new efficient, privacy-preserving, and quantum-resistant key generation algorithm, namely, lattice-based hierarchical deterministic key generation (LB-HDKG), for maintaining user privacy in the public blockchain. The LB-HDKG scheme generates many cryptographic keys in a tree-like structure from a single seed to hide the links between transactions of the same user. Our proposal uses the lattice NTRU cryptosystem, the security of which relies on the shortest vector problem (SVP) and closest vector problem (CVP) over the polynomial ring. Operations on the lattice NTRU cryptosystem are efficient and secure against classical computers and quantum computers. Security and performance analyses of our scheme show that the model is more secure and efficient and should replace current models to safeguard data from quantum computers. [ABSTRACT FROM AUTHOR]

Distributed Internet of Things (Distributed IoT) is a large-scale, heterogeneous, dynamic distributed architecture environment which is gradually formed based on Internet of Things (IoT) technology. In order to cope with the large number access requirements for IoT data brought by application expansion, the data of IoT devices are usually stored in the management server (DMS) of current domain, and adopt a centralized access control mechanism to user. This centrally approach can easily cause data to be tampered with and leaked. Moreover, registering different identities when user accesses different domains increases the difficulty to manage his identities. Therefore, this paper proposes a blockchain-based access control scheme called BacS for Distributed IoT. In BacS, firstly, we use account address of the node in blockchain as the identity to access DMS, redefine the access control permission of data of devices and store on blockchain. Then we design processes of authorization, authorization revocation, access control and audit in BacS. Finally, we use a lightweight symmetric encryption algorithm (SEA) to achieve privacy-preserving for Distributed IoT system. We build a credible experimental model on Ethereum private chain, results show that BacS is feasible and effective that it can achieve secure access in Distributed IoT environment while protecting privacy. [ABSTRACT FROM AUTHOR]

This work investigates the unified coding and identification of smart grid IoT devices, as more and more IoT devices in smart grid need to be managed and controlled. We combine blockchain technology with 5G MEC to realize the connection of massive power IoT devices at the edge of 5G network. Due to blockchain's distributed storage and credibility, it is used to identify and register IoT devices in smart grid, ensuring the reliability and accuracy of smart grid IoT devices management. In this paper, we propose a hybrid blockchain mechanism based on 5G MEC smart grid, where both public blockchain and private blockchain are deployed on the MEC gateway/server. To facilitate the data searching and extracting, we endeavor to build a blockchain explorer indexed by IoT device identifier. After that, we study the typical consensus algorithms in the blockchain such as PoW, PoS, DPoS, PDFT, and discuss their feasibility in the hybrid blockchain. Finally, we analyzed and compared the performance of different consensus algorithms from the perspective of average computing time and average time to agreement. [ABSTRACT FROM AUTHOR]

Blockchain technology considers the central technology that is used within many applications used frequently with human life. And the primary core of the blockchain is the consensus algorithm which may affect the security of the chain as well as the required resource consumption which affect mainly the blockchain performance directly. In recent years many consensus algorithms have been used and proposed such as proof of work (PoW) and proof of stake (PoS) and many others. However, these algorithms still need some improvement to the security and system resource consumption which will reduce the need for a huge amount of energy and save the environment as well as let the blockchain be useable within low computation ability devices such as the internet of things devices (IoT). This paper proposes a new consensus algorithm that ensures the integrity and authorization of nodes participating in the validation of the transaction and only a predefined number of nodes chosen randomly to participate in block addition which reduces the need for high computations power for mining and voting. The proposed algorithm needs lower time and computation costs comparable to the standard POW algorithm. [ABSTRACT FROM AUTHOR]

• Our algorithm is more efficient, has less communication overhead, and has greater throughput than the original PBFT algorithm. • We propose a Vehicle - Service Provider - Roadside Unit architecture to ensure the orderliness and safety of vehicles. • We propose an identity authentication scheme based on blockchain. • Experimental results demonstrate that our solution is better than PBFT, G-PBFT and CPBFT. As an application of Internet of Things (IoT) technology, the Internet of Vehicles (IoV) faces two main security issues: (1) the central server of the IoV may not be powerful enough to support the centralized authentication of the rapidly increasing connected vehicles, (2) the IoV itself may not be robust enough to single-node attacks. To address these issues, in this paper, we propose SG-PBFT (Score Grouping-PBFT), a secure and efficient distributed consensus algorithm for blockchain applications in the IoV. The distributed structure can reduce the pressure on the central server and decrease the risk of single-node attacks. The SG-PBFT consensus algorithm improves the traditional practical Byzantine fault tolerance (PBFT) consensus algorithm by optimizing the PBFT consensus process and using a score grouping mechanism to achieve a higher consensus efficiency. The experimental results show that the method can greatly improve the consistency efficiency and effectively prevent single-node attacks. Specifically, when the number of consensus nodes reaches 1000, the consensus time of our algorithm is only about 27% of what is required for the state-of-the-art PBFT consensus algorithm. Our proposed SG-PBFT algorithm is versatile and can be used in other application scenarios which require high consensus efficiency. [ABSTRACT FROM AUTHOR]

In view of the fact that the storage and transaction throughput problems faced by the combination of blockchain and the Internet of Things（IoT）, this paper proposed a scalable IoT model based on dual blockchains. Firstly, it designed a dual blockchain storage structure based on transaction chain and hash chain and a partition model. The differentiated storage of the transaction chains reduced the storage burden of the nodes, and the hash chain improved the overall security of the system and realized the free transaction of data in the entire network. Secondly, it proposed the PMCP, which reduced the system consensus delay, improved the system throughput and had better scalability. Finally, the reputation-based verifier and leader election algorithm ensured the randomness and fairness of node selection, avoided the problem of system centralization, and it designed a node reputation value evaluation mechanism to ensure the security of the protocol. The experimental results show that the storage capacity of the model is greatly improved compared with the traditional blockchain model, and the scalability of the blockchain system is enhanced. The performance of PMCP are significantly better than that of other protocols. The reputation mechanism encourages nodes to make rational choices, which can greatly enhance the security of the network. [ABSTRACT FROM AUTHOR]

Summary: A secure decision tree twin support vector machine (DT‐TSVM) multi‐classification algorithm has been proposed in this paper for improving the reliability and security of the collected IoT data from multiple data providers. The multiclass secure DT‐TSVM algorithm has been employed to train a machine learning model using the encrypted training dataset. The training dataset is collected via a blockchain platform. A blockchain method has been adopted to construct a secure and reliable distributed platform among dataset providers. The Paillier homomorphic cryptosystem has been applied for encrypting the IoT dataset. Then, the dataset has been recorded on the distributed ledger. The secure DT‐TSVM algorithm's‐based train model effectiveness has been compared with the other two available algorithms, namely the multiclass binary support vector machine (MBSVM) and one‐to‐one SVM algorithms. The experiment results showed that the privacy‐preserving multiclass secure DT‐TSVM‐based model did not reduce the accuracy, but it increased the average precision and recall by 0.53% and 0.44% than MBSVM and 0.82% and 0.71% than one‐to‐one SVM, respectively. Further, the time consumption of data providers and data analysts did not change significantly with the increase of number of data provider. [ABSTRACT FROM AUTHOR]

Compared with the traditional blockchain, blockchain sharding system has higher throughput and is more suitable for the Internet of Things (IoT) with massive data. The sharding algorithm determines how to divide nodes into different shards. However, the existing sharding algorithms ignore the resource requirements of a shard, the resource heterogeneity and the closeness of relationship between the IoT devices, which hinders the application of sharding technology in IoT. In order to solve this problem, we propose a blockchain sharding algorithm based on trust field model (STFM). Nodes can join the most suitable shard according to the shard requirements, the resources they owned and the closeness of relationship with leader of the shard. The experimental results show that the nodes in the shards formed by STFM have a closer relationship, and distribution of resource intensity and trust level between the shards is more balanced, which can effectively improve system throughput and security. [ABSTRACT FROM AUTHOR]

With the advent of the Industry 4.0 era, the development of smart cities based on the Internet of Things (IoT) has reached a new level. As a key component of the Internet of Things (IoT), the security of wireless sensor networks (WSN) has received widespread attention. Among them, Energy Internet, as an important part to support the construction of smart cities, its security and reliability research is becoming more and more important. In the Energy Internet, distributed energy transaction model is a promising approach to replace the traditional centralized transaction model and has become the leading direction of development in energy trading. As the underlying support, blockchain technology is attracting more and more attention due to its advantages, i.e., integrity and non-repudiation. However, most blockchain-based trading models face the problem of privacy disclosure. In this paper, to solve this problem, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is introduced as the core algorithm to reconstruct the transaction model. Specifically, we build a general model for distributed transactions called PP-BCETS (Privacy-preserving Blockchain Energy Trading Scheme). It can achieve fine-grained access control through transaction arbitration in the ciphertext form. This design can maximize the protection of privacy information, and considerably improve the security and reliability of the transaction model. Additionally, a credibility-based equity proof consensus mechanism is proposed in PP-BCETS, which can greatly increase the operation efficiency. The security analysis and experimental evaluations are conducted to prove the validity and practicability of our proposed scheme. • Secure and privacy-preserving energy trading scheme is proposed. • ABE- and blockchain-based energy trading. • credibility-based equity proof consensus mechanism. [ABSTRACT FROM AUTHOR]

In order to solve the security and scalability of centralized management of large-scale IoT devices, this paper proposed a scalable management framework for lightweight IoT devices based on blockchain technology. The framework used a blockchain network, deployed smart contracts in the network to provide an operational interface for device management, used device managers to separate lightweight Io T devices from block chain networks, and improved Byzantine fault tolerance in blockchains, the algorithm( PBFT) consistency protocol added a dynamic election mechanism. The simulation experiments verify the performance and mechanism scalability of the improved consensus algorithm. The results show that the mechanism has good scalability, and the device manager can respond to about 1 000 requests per second. Compared with the traditional PBFT algorithm, the improved algorithm improves transaction throughput, reduces transaction latency, and reduces communication overhead. [ABSTRACT FROM AUTHOR]

Blockchain technology may provide a potential solution to the Internet of Things (IoT) security challenges by providing a decentralized and secure method for storing, managing, and sharing data. The Secure Hash Algorithm (SHA-256) hashed value of preliminary data (block) is retained in one block along with transaction data in tree form and timestamp in a chain of blocks. However, there are observations about blockchain limitations such as higher energy consumption, secure data, self-maintenance reliance, and higher cost. These constraints can be overcome by incorporating encryption algorithms into accepting blocks of data. In this paper, we propose a secure intelligent computational model for a large-scale interconnected IoT environment; an analytical modeling technique is considered for the proposed system. The proposed system takes advantage of the potential security feature of blockchain, which is considered the most appropriate secure communication system in an IoT. A computational model is built using the proposed blockchain technology to incorporate a secure and intelligent communication system. The proposed system uses the enhanced McEliece encryption approach's potential to link the blockchain due to the faster mode of encryption and decryption process with a highly reduced number of steps. [ABSTRACT FROM AUTHOR]

One of the integral components in the architectural design and development of Internet of Things (IoT) is Microservice. Microservices are basically an architectural and organizational approach in the process of software development where the software is composed of small but independent services that would communicate over well-defined APIs (Application Programming Interfaces). It is quite challenging to ensure data integrity and data availability in the architecture design of microservices. As Blockchain technology has emerged as a panacea to many of the other domains, the distributed microservice architecture can also utilize it. We know that the consensus algorithms are used in the Blockchain technology to validate the transactions alongside providing extra level of security. Taking the advantage of consensus algorithms in blockchain-based architecture models, in this paper, we propose TCA (Trustworthy Consensus Algorithm), which is designed to solve the data integrity and availability challenges in microservice architectures. We have evaluated the proposed algorithm against the known alternatives and it shows good level of efficiency. [Display omitted] • One of the integral components of Internet of Things (IoT) is Microservice. • It is a challenge to ensure data integrity and data availability. • The consensus algorithms in blockchain provide extra level of security. • Trustworthy Consensus Algorithm enhances the security of microservice. [ABSTRACT FROM AUTHOR]

Presented herein is a novel algorithm for multi-round, zero-knowledge proof (ZKP), devised specifically for authenticating factorisation proofs within a variety of cryptographic applications. This advanced algorithm, while maintaining computational complexity within acceptable bounds, offers a secure and proficient solution. The functionality of the algorithm is marked by multiple rounds of interaction between the Prover and Verifier. Initially, the Prover generates a random value and calculates a commitment. Subsequently, the Verifier issues a random challenge, eliciting a computed response from the Prover. To validate the proof, the Verifier verifies the equality of the commitment and the computed response. Efficaciousness of the proposed multi-round ZKP algorithm is demonstrated across diverse input sizes and parameters. Results indicate a success rate exceeding 90% on average, showcasing the robustness of the method. The recurring interaction between the Verifier and Prover enhances the Prover's authentication, thereby improving the algorithm's reliability. Implementation of the algorithm, achievable through standard cryptographic tools and protocols, can fortify the security of multiple cryptographic applications. A significant application can be found in Digital Identity Management Systems (DIMS). Currently, these systems are vulnerable to a myriad of threats, including identity spoofing, data breaches, and internal security risks. The application of the ZKP algorithm can simultaneously augment security and withhold sensitive information, potentially transforming the DIMS security landscape. Future research may focus on improving the efficiency and scalability of the multi-round ZKP algorithm. There also remains a vast potential for exploring additional applications of this technique within various cryptographic domains. [ABSTRACT FROM AUTHOR]

The rapid advancement in artificial intelligence (AI) and wide deployment of Internet of Video Things (IoVT) enable situation awareness (SAW). The robustness and security of IoVT systems are essential for a sustainable urban environment. While blockchain technology has shown great potential in enabling trust-free and decentralized security mechanisms, directly embedding cryptocurrency oriented blockchain schemes into resource-constrained Internet of Video Things (IoVT) networks at the edge is not feasible. By leveraging Electrical Network Frequency (ENF) signals extracted from multimedia recordings as region-of-recording proofs, this paper proposes EconLedger, an ENF-based consensus mechanism that enables secure and lightweight distributed ledgers for small-scale IoVT edge networks. The proposed consensus mechanism relies on a novel Proof-of-ENF (PoENF) algorithm where a validator is qualified to generate a new block if and only if a proper ENF-containing multimedia signal proof is produced within the current round. The decentralized database (DDB) is adopted in order to guarantee efficiency and resilience of raw ENF proofs on the off-chain storage. A proof-of-concept prototype is developed and tested in a physical IoVT network environment. The experimental results validated the feasibility of the proposed EconLedger to provide a trust-free and partially decentralized security infrastructure for IoVT edge networks. [ABSTRACT FROM AUTHOR]

Recently, to enhance the security of the Internet of Things (IoT), research on blockchain-based encryption algorithms has been actively conducted. However, because blockchains have complex structures and process large amounts of data, there are still many difficulties in using the conventional blockchain-based encryption algorithms in an IoT system that must have low power consumption and be ultra-lightweight. In this study, to address these problems (1) we simplified the conventional Directed Acyclic Graph (DAG)-based blockchain structure, and (2) we proposed a new Advanced Encryption Standard (AES)-Cipher Block Chaining (CBC) algorithm with enhanced security by periodically changing the secret key and initialization vector (IV) in the conventional AES-CBC encryption algorithm. Because the DAG, which is the conventional blockchain structure, randomly transmits data to multiple blocks, there may be overlapping blocks, and the quantity of transmitted data is not limited; thus, the time and power consumption for encryption and decryption increase. In this study, a simplified DAG was designed to address these problems so that packets can be transmitted only to three blocks, without overlapping. Finally, to verify the effectiveness of the algorithm proposed in this paper, an IoT system consisting of 10 clients and one server was implemented in hardware, and an experiment was conducted. Through the experiment, it was confirmed that when the proposed AES-CBC algorithm was used, the time taken and the amount of power consumed for encryption and decryption were reduced by about 20% compared to the conventional AES-CBC algorithm. [ABSTRACT FROM AUTHOR]

Several unique characteristics of Internet of Things (IoT) devices, such as distributed deployment and limited storage, make it challenging for standard centralized access control systems to enable access control in today’s large-scale IoT ecosystem. To solve these challenges, this study presents an IoT access control system called Ether-IoT based on the Ethereum Blockchain (BC) infrastructure with Attribute-Based Access Control (ABAC). Access Contract (AC), Cache Contract (CC), Device Contract (DC), and Policy Contract (PC) are the four central smart contracts (SCs) that are included in the proposed system. CC offers a way to save user characteristics in a local cache system to avoid delays during transactions between BC and IoT devices. AC is the fundamental program users typically need to run to build an access control technique. DC offers a means for storing the resource data created by devices and a method for querying that data. PC offers administrative settings to handle ABAC policies on users’ behalf. Ether-IoT, combined with ABAC and the BC, enables IoT access control management that is decentralized, fine-grained and dynamically scalable. This research gives a real-world case study to illustrate the suggested framework’s implementation. In the end, a simulation experiment is performed to evaluate the system’s performance. To ensure data integrity in dispersed systems, the results show that Ether-IoT can sustain high throughput in contexts with a large number of requests. [ABSTRACT FROM AUTHOR]

Blockchain technology is increasingly being used in Internet of things (IoT) devices for information security and data integrity. However, it is challenging to implement complex hash algorithms with limited resources in IoT devices owing to large energy consumption and a long processing time. This paper proposes a RISC-V processor with memristor-based in-memory computing (IMC) for blockchain technology in IoT applications. The IMC-adapted instructions were designed for the Keccak hash algorithm by virtue of the extendibility of the RISC-V instruction set architecture (ISA). Then, a RISC-V processor with area-efficient memristor-based IMC was developed based on an open-source core for IoT applications, Hummingbird E200. The general compiling policy with the data allocation method is also disclosed for the IMC implementation of the Keccak hash algorithm. An evaluation shows that >70% improvements in both performance and energy saving were achieved with limited area overhead after introducing IMC in the RISC-V processor. [ABSTRACT FROM AUTHOR]

Health Internet of Things (Health IoT) has been limited by isolated information and a lack of security. As the combination of blockchain and Health IoT could potentially address these two limitations, it has attracted significant interest. However, blockchain‐based systems often fail to balance data sharing and privacy protection. Therefore, we proposed a Health IoT‐based privacy‐preserving data sharing blockchain system. We designed a privacy‐preserving method based on the content extraction signature scheme to enable patients to establish fine‐grained privacy protection. We designed a Byzantine fault‐tolerant leader election mechanism that enhances the security of the Raft algorithm while providing efficiency in the data sharing. Furthermore, we designed a summary contract to ensure efficient data retrieval. The proposed mechanism was evaluated in terms of the efficiency and security. The simulation and analysis results demonstrate that our scheme offers a secure and effective technique for achieving privacy‐preserving and efficient sharing of IoT medical data. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has been making people's lives more efficient and more comfortable in the past years, and it is expected to get even better. This improvement may benefit from the use of blockchain to enhance security, scalability, reliability and auditability. Recently, different blockchain architectures were proposed to provide a solution that is better suited for IoT scenarios. One of them, called appendable-block blockchains, proposed a data structure that allows to include transactions in blocks that were already inserted in the blockchain. This approach allows appendable-block blockchains to manage large amounts of data produced by IoT devices through decoupled and appendable data structures. Nevertheless, consensus algorithms can impact throughput and latency in scenarios with large amount of produced transactions, since IoT devices can produce data very quickly (milliseconds) while these data might take some time to be included in a block (seconds). Consequently, it is important to understand the behaviour of different consensus algorithms over appendabble-block blockchain in these type of scenarios. Therefore, we adapted the appendable-block blockchain to use and compare the impact of different consensus algorithms: Practical Byzantine Fault Tolerance (PBFT), witness-based, delegated Byzantine Fault Tolerance (dBFT) and Proof-of-Work (PoW). The results show that both dBFT and PBFT can achieve fast consensus (< 150ms) in the context of appendable-block blockchains. We also present a discussion regarding attacks in each consensus algorithm to help one to choose the best solution (considering performance and security issues) for each scenario. [ABSTRACT FROM AUTHOR]

As the number of devices joining the Internet of Things (IoT) keeps increasing, vast amounts of data are being mined, and data sharing can exploit their considerable value. Owing to its advantages of decentralization, consistency, and traceability, blockchain technology can be used to build an efficient and reliable IoT data sharing system. To facilitate the use of blockchain in IoT devices, we design a new slicing- and coding-based consensus algorithm (SCCA). The proposed consensus algorithm considers the storage optimization of the blockchain ledger. Specifically, the SCCA slices and encodes consensus resources and divides the blockchain nodes into different domains. It allows multiple domains to perform consensus concurrently and collaborate to store the blockchain ledger. Finally, we construct an experimental platform and evaluate the scheme. Experimental results reveal that the SCCA can increase throughput by more than five times and reduce communication costs by 95.7%, compared to the practical Byzantine fault tolerance method. In addition, the SCCA can reduce the storage cost of a single node to approximately 28.5% of that of the Bitcoin system. [ABSTRACT FROM AUTHOR]

In this work we describe and analyze a novel multi-tier architecture for recording Internet of Things (IoT) data. Each tier in the architecture consists of vertically interconnected node clusters that may be operated by different service providers. Blocks of IoT data are accepted by a cluster tier by tier, until they reach the top tier which adds them to the global blockchain and makes them available to client applications. To allow for large geographical coverage and reduce the dependency on any individual node in the cluster, clusters run a multiple entry version of the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm. We describe an analytical model of the system and find the optimal allocation of clusters and nodes within clusters for a given number of tiers and system coverage area. Our results show that the total number of orderers for given system coverage and total load are main predictors of the block linking time, and indicate that minimizing block linking time is easier to achieve with a smaller number of tiers and large number of clusters with a smaller number of orderers per cluster. These observations can be used as guidelines for planning and dimensioning of multi-tier cluster architectures that create and maintain blockchain structures in a given coverage area. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) is expected to improve our lifestyle in a noticeable way. However, although the IoT holds a lot of chances, it contains a lot of serious risks. This leads to a focus on developing security techniques that can increase the security level of IoT. Blockchain is considered as an innovative technique for securing IoT and sharing data in a secure and tamperproof way. The blockchain is a peer-to-peer connection system that performs transactions securely by using consensus algorithms with no need for a trusted third party. Blockchain proved its applicability in securing IoT networks, and the research in this area is still enticing researchers to delve deeper and deeper. Decentralized voting is considered the fundamental principle that blockchain relies on for making the appropriate decision that would offer a proper security level for IoT. In this research a novel decentralized blockchain Weighted Majority Consensus Algorithm is proposed. The algorithm is inspired by the well-known weighted majority voting algorithm in the ensemble data mining learning approach. A java implementation of WMCA has been created for testing several scenarios with the aim of confirming the applicability of the proposed WMCA and the results were very promising. [ABSTRACT FROM AUTHOR]

Blockchain offers new ways to the data sharing-based collaboration among IoT devices when a centralized IT infrastructure is unavailable. As one of the critical elements in a Blockchain system, the existing consensus algorithms still have some weaknesses, such as energy-wasting, low throughput, high latency, and increased network communication requirements. In this paper, we focus on designing a highly efficient Blockchain consensus algorithm for data sharing among IoT devices. We present the detailed design of Teegraph, which is a Trusted Execution Environment (TEE) and Directed Acyclic Graph (DAG)-based consensus algorithm. A proof-of-concept implementation of Teegraph is presented. The simulation results demonstrate that TEE usage in Teegraph is more efficient than that of the existing state of the art TEE-based consensus algorithms such as MinBFT and MinZyzzyva. Moreover, Teegraph outperforms Hashgraph, one of the most popular DAG-based consensus algorithms in throughput and latency. [ABSTRACT FROM AUTHOR]

Artificial Internet of Things (AIoT) is that the system collects all kinds of information in real-time through various sensors, and intelligence analysis of the data through machine learning in the terminal equipment, edge domains, or cloud centers, including positioning, comparison, forecasting, scheduling, etc. which brings about the data security and privacy issues. The blockchain is a tamper-evident, unforgeable distributed ledger that protects security and privacy through the famous algorithm zk-SNARK, which is also widely used in virtual digital currencies such as Zcash. In addition, by using zk-SNARK technology in the Loopring DEX 3.0 in Ethereum, not only decentralization but also transaction performance can be guaranteed. However, there are three main problems of zk-SNARK, one is the need to guarantee calculation accuracy, two is the long time to generate evidence, especially when using Lagrangian interpolation to QAP the transaction data requires more computation; the last is the poor scalability, especially when nodes need to recalculate all data when adding new transactions. In this paper, we propose a modified zk-SNARK based on Newtonian interpolation, improve the QAP part of zk-SNARK by Newtonian interpolation, and verify the correctness of the scheme through instantiation. Finally, we analyze the computational efficiency of the two interpolation methods, and the results show that Newton interpolation solves the above two problems in the original zk-SNARK, and significantly reduces the time complexity of the algorithm, which can further promote the application of blockchain in data management of AIoT. [ABSTRACT FROM AUTHOR]