Due to the explosive increase in IoT devices and traffic, big data is developing into smart data that helps the data science experts understand human activities, through the relationship between mobility and resource ...
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Due to the explosive increase in IoT devices and traffic, big data is developing into smart data that helps the data science experts understand human activities, through the relationship between mobility and resource application of the users in public spaces. For example, smart data markets help to predict crimes or understand the cause of COVID-19 infections. For these smart services, the users agree to the privacy policy so that the personal and sensitive information can be collected by a third party. But the conditions of the privacy policy do not specify whether the information of the users can be tracked. To ensure data transparency, many systems are applying consortium/private blockchains with raft algorithm. The raft algorithm requires nodes to check countless messages for a single transaction. Eventually, as the number of nodes increases, the overall system degradation is derived from the burden of the leader node. This paper proposes a method to process the collected transactions by dividing a certain amount of transactions into cells, without any extra protocol. The proposed scheme also uses the federated learning model with high accuracy and data privacy, in order to determine the optimized cell size in a blockchain system that should lead to consensus on multiple servers. Therefore, the proposed CBR (Cell-based raft) consensus algorithm proposes a protocol that reduces the number of messages, without interfering with the concept of the existing raft algorithm, in order to maintain stable throughput in the smart data market where massive transactions occur.
raft is a consensus algorithm that implements highly available replicas. As raft requires a leader to drive the protocol execution, it usually employs a round-robin leader election mechanism to select a random leader ...
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raft is a consensus algorithm that implements highly available replicas. As raft requires a leader to drive the protocol execution, it usually employs a round-robin leader election mechanism to select a random leader among all nodes. However, when the elected leader suffers from performance issues, the protocol will temporarily lose aliveness. To address this issue, we propose a multi-strategy leader election mechanism that allows nodes to proactively trigger a new round of election when they believe the leader suffers from performance issues, and replace this leader with a new one in a designated priority queue. The formal analysis and experimental results show that the mechanism can improve the system's throughput/latency without additional election time overhead.
To optimize the Byzantine fault tolerance of raft algorithm, a Byzantine fault-tolerant B-raft algorithm combined with Schnorr signature mechanism is proposed. First, during leader election, followers are required to ...
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ISBN:
(纸本)9781665423182
To optimize the Byzantine fault tolerance of raft algorithm, a Byzantine fault-tolerant B-raft algorithm combined with Schnorr signature mechanism is proposed. First, during leader election, followers are required to sign the ballot to prevent the Byzantine node from forging the vote. Second, the client is required to sign the message when sending the message to leader to prevent the Byzantine leader from tampering with the logs. B-raft combines the signature mechanism with the raft algorithm and several modifications and additions provide Byzantine fault tolerance. The results of the experiments launched in Hyperledger Fabric show that compared with the raft algorithm, the safety of B-raft is greatly improved.
To address the issue that existing raft consensus algorithms in blockchain cannot achieve low latency, high security, and high efficiency simultaneously, a raft consensus algorithm based on reputation regression and R...
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ISBN:
(纸本)9798350389913;9798350389906
To address the issue that existing raft consensus algorithms in blockchain cannot achieve low latency, high security, and high efficiency simultaneously, a raft consensus algorithm based on reputation regression and RSA signatures, named RR-raft, is designed. The algorithm first introduces a reputation measurement function and a reputation consumption function into the Logistic regression algorithm, constructing a reputation model based on R-Logistic regression. This model solves the centralized reputation problem in traditional regression algorithms, thereby enhancing the enthusiasm of nodes for consensus. Secondly, to address the issue of vote splitting during the leader election phase of the consensus mechanism, a quick leader node election strategy based on the reputation model is proposed to improve consensus efficiency. Lastly, to prevent the Leader node from tampering with the logs as a malicious actor, a fast RSA aggregate signature based on Barrett reduction is proposed to enhance the security of consensus.
Existing vehicle platooning creates platooning of vehicles with the same destination, and the leader vehicle manages the platooning. Since there is no way to elect a leader vehicle for platooning management, and the l...
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ISBN:
(纸本)9781728113395
Existing vehicle platooning creates platooning of vehicles with the same destination, and the leader vehicle manages the platooning. Since there is no way to elect a leader vehicle for platooning management, and the leader vehicle has not changed since its initial election, it is difficult to cope with the traffic situation in real time. To complement this, it is proposed that the raft algorithm is applied to automatically elect the appropriate leader vehicle. To verify this, the proposed platooning was analyzed by comparing them according to the platooning scenarios to confirm that flexible platooning is possible.
To address the limitations of the raft consensus algorithm, such as the lack of support for Byzantine fault tolerance, performance bottleneck of the leader single node, and high leader election delay, an improved Byza...
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To address the limitations of the raft consensus algorithm, such as the lack of support for Byzantine fault tolerance, performance bottleneck of the leader single node, and high leader election delay, an improved Byzantine fault tolerance consensus algorithm called RaBFT based on raft is proposed. The distribution process of log messages is optimized by utilizing the secret sharing technique to make it Byzantine fault tolerance, and the role of the committee is introduced to share the communication pressure of the leader, thereby resolving the performance bottleneck issue of the leader single node. The leader election algorithm based on a dynamic committee improves the speed of leader election and reduces the time required for leader election. The experimental results show that RaBFT algorithm has a significant improvement in throughput and consensus delay in the log replication phase, and has a lower leader election delay, RaBFT algorithm can improve the efficiency and performance of the system, it is a safe and efficient consensus algorithm.
Blockchain technology has gained significant attention and widespread adoption due to several key factors, such as immutability, higher security, decentralization, transparency, smart contracts and automation, efficie...
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Blockchain technology has gained significant attention and widespread adoption due to several key factors, such as immutability, higher security, decentralization, transparency, smart contracts and automation, efficiency and cost savings, and the potential for innovation in numerous industries, including finance, healthcare, supply chain, real estate, education sector, and many more. Nowadays, the forgery of educational certificates is a concerning issue that poses significant challenges to academic institutions, employers, and individuals seeking authentic qualifications. Here, we propose a secure and notarized educational certificate authentication and verification framework named EduCert-Chain using Hyperledger Fabric to overcome concerns. EduCert-Chain uses ECDSA (Elliptic Curve Digital Signature algorithm) for digital signature and verification, the SHA-256 algorithm for cryptographic hashing, and the raft consensus mechanism for validating network transactions. We have used the Hyperledger Caliper tool to conduct an extensive set of experiments to evaluate the performance of the proposed framework in terms of throughput and latency. We have considered two HEIs (Higher Education Institutions) organizations for the experimental evaluations, and the transaction ranges between 50-500. We have used CouchDB as a state database and the Docker container to handle highly portable workloads. Our framework achieves an average throughput for the query function, which is 34.95 TPS, and for the open function, it is 32.23 TPS. Additionally, it achieves an average latency of 4.21 s for the query function and 2.05 s for the open function. We also have conducted a comparative analysis to assess security features and limitations between the proposed framework and related work. Our observation reveals that the proposed EduCert-Chain framework has better features. This initiative will positively contribute towards addressing the issues of fraudulent credentials and forgery.
To achieve automation and intelligence in 5G networks, the 3rd Generation Partnership Project (3GPP) introduced the Network Data Analysis Function (NWDAF) as a novel network function. However, in the traditional 5G co...
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ISBN:
(纸本)9789819722747;9789819722754
To achieve automation and intelligence in 5G networks, the 3rd Generation Partnership Project (3GPP) introduced the Network Data Analysis Function (NWDAF) as a novel network function. However, in the traditional 5G core network architecture, NWDAF relies on fixed configurations for data collection, lacking support for user customization and flexibility. Additionally, the current deployment of NWDAF is predominantly centralized, failing to provide real-time and reliable analysis services for the massive data in future 6G systems. Moreover, it is incapable of ensuring user privacy, making it incompatible with emerging scenarios like federated learning in 6G. Therefore, this paper proposes a user-customizable data collection approach and introduces a distributed NWDAF deployment based on the raft algorithm, where the master node assigns data collection, analysis, and inference tasks to multiple worker NWDAFs. Our work and experimental results demonstrate that the proposed architecture effectively addresses these challenges and further achieves closed-loop network automation in 6G systems.
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...
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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.
Many MANET research works are based on the popular informal definition that MANET is a wireless ad-hoc network that has neither infrastructure nor backbone and every network node is autonomous and moves depending on i...
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Many MANET research works are based on the popular informal definition that MANET is a wireless ad-hoc network that has neither infrastructure nor backbone and every network node is autonomous and moves depending on its mobility. Unfortunately, this definition pays no attention to the network servers that are essential in core-based, mission-critical, and military MANETs. In core-based MANETs, external intrusion detection systems (IDS) cannot detect internal Byzantine attacks;in addition, internal Byzantine fault tolerant (BFT) systems are unqualified to detect typical external wireless attack. Therefore, there is a real need to combine both internal and external mobile ad-hoc network (MANET) ID systems. Here, CSMCSM is presented as a two-level client server model for comprehensive security in MANETs that integrates internal and external attack detectors in one device. The internal component is based on a BFT consensus algorithm while the external component employs decision tree to classify the MANET attacks.
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