TCNS: Node Selection With Privacy Protection in Crowdsensing Based on Twice Consensuses of Blockchain

An, Jian; He, Yang; Gui, Xiaolin; Zhang, Wendong; Gui, Ruowei; Kang, Jingjing

doi:10.1109/tnsm.2019.2920001

Cited by 39 publications

(16 citation statements)

References 30 publications

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“…They also analyzed the security threshold based on the faulty probability determined and the faulty number determined models. An et al [37] proposed a decentralized privacy-preserving model based on the twice verifications process and consensuses of the blockchain system. They introduced a twice consensus mechanism, ensuring that data can be traced and prevented from being impersonated and denied.…”

Section: Related Workmentioning

confidence: 99%

A Hierarchical and Location-Aware Consensus Protocol for IoT-Blockchain Applications

Guo

Nejad

2022

IEEE Trans. Netw. Serv. Manage.

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Blockchain-based IoT systems can manage IoT devices and achieve a high level of data integrity, security, and provenance. However, incorporating existing consensus protocols in many IoT systems limits scalability and leads to high computational cost and consensus latency. In addition, locationcentric characteristics of many IoT applications paired with limited storage and computing power of IoT devices bring about more limitations, primarily due to the location-agnostic designs in blockchains. We propose a hierarchical and location-aware consensus protocol (LH-Raft) for IoT-blockchain applications inspired by the original Raft protocol to address these limitations. The proposed LH-Raft protocol forms local consensus candidate groups based on nodes' reputation and distance to elect the leaders in each sub-layer blockchain. It utilizes a threshold signature scheme to reach global consensus and the local and global log replication to maintain consistency for blockchain transactions. To evaluate the performance of LH-Raft, we first conduct an extensive numerical analysis based on the proposed reputation mechanism and the candidate group formation model. We then compare the performance of LH-Raft against the classical Raft protocol from both theoretical and experimental perspectives. We evaluate the proposed threshold signature scheme using Hyperledger Ursa cryptography library to measure various consensus nodes' signing and verification time. Experimental results show that the proposed LH-Raft protocol is scalable for large IoT applications and significantly reduces the communication cost, consensus latency, and agreement time for consensus processing.

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Section: Related Workmentioning

confidence: 99%

A Hierarchical and Location-Aware Consensus Protocol for IoT-Blockchain Applications

Guo

Nejad

2022

IEEE Trans. Netw. Serv. Manage.

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“…Huang et al [44] combine blockchain with crowd-sense in an industrial system, while Hu et al [45] propose a crowd-sense incentive mechanism based on blockchain. An et al [46] provide a decentralized crowd-aware model with an anonymity policy based on an elliptic curve algorithm verification scheme that is employed to protect the users' identity privacy. Kadadha et al [47] utilize the decentralized characteristics of the blockchain to enable multitasking and multi-user task assignment and to protect user privacy.…”

Section: Related Workmentioning

confidence: 99%

A Privacy-Preserving Mobile Crowdsensing Scheme Based on Blockchain and Trusted Execution Environment

Peng

Guan

Liu

2022

IEICE Trans. Inf. & Syst.

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A mobile crowdsensing system (MCS) utilizes a crowd of users to collect large-scale data using their mobile devices efficiently. The collected data are usually linked with sensitive information, raising the concerns of user privacy leakage. To date, many approaches have been proposed to protect the users' privacy, with the majority relying on a centralized structure, which poses though attack and intrusion vulnerability. Some studies build a distributed platform exploiting a blockchain-type solution, which still requires a fully trusted third party (TTP) to manage a reliable reward distribution in the MCS. Spurred by the deficiencies of current methods, we propose a distributed user privacy protection structure that combines blockchain and a trusted execution environment (TEE). The proposed architecture successfully manages the users' privacy protection and an accurate reward distribution without requiring a TTP. This is because the encryption algorithms ensure data confidentiality and uncouple the correlation between the users' identity and the sensitive information in the collected data. Accordingly, the smart contract signature is used to manage the user deposit and verify the data. Extensive comparative experiments verify the efficiency and effectiveness of the proposed combined blockchain and TEE scheme.

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“…An et al 41 suggested a segregated privacy protecting method in node selection of crowd sensing systems. TCNS is based on double confirmation and consensuses of blockchain and the anonymity method confirmed by consensuses.…”

Section: Blockchain Technology On Energy‐aware Mobile Crowd Sensingmentioning

confidence: 99%

Blockchain technology for energy‐aware mobile crowd sensing approaches in Internet of Things

Sisi

Souri

2021

Trans Emerging Tel Tech

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Today, Blockchain technology is emerging to support high secured performance computing. To improve privacy and security factors of allocate, storage, and manage resources in edge computing, blockchain technology can be used to guarantee safe data transmission and communications in Internet of Things (IoT). Due to heterogeneity of resources to cover a range number of IoT applications, resource allocation has a key role for increasing performance of the IoT systems in edge computing. Also, a blockchain‐based resource allocation model can support Quality of Service (QoS) for IoT applications to ensure a high secured communication environment in edge computing. This paper reviews different existing green energy strategies based on blockchain technology in mobile crowd sensing. Mobile crowd sensing refers to all computational aspects related to smart city, smart home‐care, smart grid, smart transportations, smart medical systems, smart industry, manufacturing, and smart farming in IoT environments. This review aims to classify principles and technical aspects of green energy strategies based on blockchain technology in mobile crowd sensing with respect to technical aspects, applied algorithms, evaluation factors, and evaluation environments. Based on Systematic Literature Review (SLR), we selected 37 high potential and key relevant research studies to consider in this review. Based on analytical results, 35% of them were considered as private‐based blockchain methods, 33% of them were applied to the public‐based blockchain methods, 24% of them were considered as consortium‐based blockchain methods, and 8% of them were as hybrid‐based blockchain methods.

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TCNS: Node Selection With Privacy Protection in Crowdsensing Based on Twice Consensuses of Blockchain

Cited by 39 publications

References 30 publications

A Hierarchical and Location-Aware Consensus Protocol for IoT-Blockchain Applications

A Hierarchical and Location-Aware Consensus Protocol for IoT-Blockchain Applications

A Privacy-Preserving Mobile Crowdsensing Scheme Based on Blockchain and Trusted Execution Environment

Blockchain technology for energy‐aware mobile crowd sensing approaches in Internet of Things

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