Permissioned Blockchain-Based Anonymous and Traceable Aggregate Signature Scheme for Industrial Internet of Things

Tian, Li; Wang, Huaqun; He, Debiao; Yu, Jia

doi:10.1109/jiot.2020.3045451

Cited by 32 publications

(7 citation statements)

References 40 publications

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“…It creates a block which has the parameters essential to make the system achieve immutable and nontampering. The transactions in the block are encrypted with its public key to ensure privacy [24]. It now requests leader for adding the block to the Network.…”

Section: Scenariomentioning

confidence: 99%

Blockchain-Based Robust Data Security Scheme in IoT-Enabled Smart Home

Vangala¹,

Das²,

Jamal³

2022

Computers, Materials &Amp; Continua

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The recent surge in development of smart homes and smart cities can be observed in many developed countries. While the idea to control devices that are in home (embedded with the Internet of Things (IoT) smart devices) by the user who is outside the home might sound fancy, but it comes with a lot of potential threats. There can be many attackers who will be trying to take advantage of this. So, there is a need for designing a secure scheme which will be able to distinguish among genuine/authorized users of the system and attackers. And knowing about the details of when and what IoT devices are used by the user, the attacker can trace the daily activities of user and can plan an attack accordingly. Thus, the designed security scheme should guarantee confidentiality, anonymity and un-traceability. Most of the schemes proposed in the literature are either non-blockchain based which involves inherent problems of storing data in a single-server or assuming weaker attack models. In this work, we propose a novel scheme based on blockchain technology, assuming a stronger Canetti and Krawczyk (CK)-threat model. Through the formal and informal security, and comparative analysis, we show that the proposed scheme provides a superior security and more functionality features, with less communication cost and comparable computational cost as compared to other competent schemes. Moreover, the blockchain based simulation study on the proposed scheme has been conducted to show its feasibility in real-life application.

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Section: Scenariomentioning

confidence: 99%

Blockchain-Based Robust Data Security Scheme in IoT-Enabled Smart Home

Vangala¹,

Das²,

Jamal³

2022

Computers, Materials &Amp; Continua

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“…where weight vector among the invisible and output layer is mentioned as W YX , node state vector is represented as P C (n) and for context and invisible layers with (n) number of nodes is calculated using Equations ( 2) and (3).…”

Section: Generalized Security Mechanism Using Eesnn For Detecting Int...mentioning

confidence: 99%

“…Increased research effort is used for improving the routing protocols, scheduling the tasks, energy efficiency, and other numerous aspects of internet of things. Nevertheless, without any sufficient security measures, IoT process is proved to be an impossible and unacceptable future fields 3 . Moreover, the IoT applications are developed a huge amount of private data are subjected to be different than the security threats, requirements to be protected 4 .…”

Section: Introductionmentioning

confidence: 99%

Enhanced Elman spike neural network fostered blockchain framework espoused intrusion detection for securing Internet of Things network

Vadi¹,

Abidin

Khan³

et al. 2022

Trans Emerging Tel Tech

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In general, due to the complexity and limited computation capabilities, the security issues occur in Internet of Things (IoT). Security protocols are required to increase the security of the system. Therefore, in this article, an enhanced Elman spike neural network (EESNN) with green proof of work consensus algorithm (GPoW) is proposed for enhancing the security of IoT network. Initially, the generalized security mechanism as EESNN approach is proposed for the IoT network by categorizing the devices into malicious and benign. Then, the GPoW consensus algorithm is used for enhancing the security of the devices from malicious attacks. Subsequently, a coalition formation (CF) algorithm is used for reducing the excess energy consumption in a network. The proposed EESNN‐GPoW‐CF approach has effectively classified the malicious attacks and enhances the security of the IoT network. The simulation of this work is done in Python. From the simulation, the proposed EESNN‐GPoW‐CF approach attains high efficiency outcomes in terms of accuracy, recall, precision, PDR, PLR, throughput, overhead, computation time, and delay. Moreover, the proposed EESNN‐GPoW‐CF approach attains 3.1%, 5.3%, 7.4% high accuracy rate, and 7.5%, 12.5%, 14.7% lower computation time with 4.8%, 2.3%, 5.7% lower energy utilization than the existing methods, such as deep learning based blockchain for IoT security, deep reinforcement learning based blockchain for IoT security, and deep blockchain‐based trustworthy privacy preserving secured framework in IoT, respectively.

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“…Furthermore, the centralized database storage also makes its transaction data easy to be tampered with. However, the blockchain technology can greatly improve the trust between various industrial participants and avoid the trust risks by breaking the data island [18]. The industrial blockchain can further improve and optimize business processes, improve collaboration efficiency, reduce operation costs, and realize the construction of trusted system [19].…”

Section: Relevant Workmentioning

confidence: 99%

A Quantum Blind Multi-Signature Method for the Industrial Blockchain

Cai

Shi

Han

et al. 2021

Entropy

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Traditional anti-quantum methods and multi-signature technologies to secure the blockchain against quantum attacks will quickly reduce the efficiency and scalability of the industrial blockchain, where the computational resources will experience a polynomial rise with the increasing number of traders. Here, a quantum blind multi-signature method is proposed for the multi-party transaction to provide anti-quantum security. First, the proposed multi-party transaction frame and quantum key distribution in the industrial blockchain are introduced. It integrates a novel quantum blind multi-signature algorithm that is based on the quantum entanglement mechanism, and it is absolutely secure in theory. Second, the anti-quantum multi-signature algorithm is illustrated, where there are four phases, i.e., initialization, signing, verification, and implementation. Third, the security and complexity of the proposed framework are analyzed and compared with related methods in references, and our proposed method is verified to be able to offer good computational performance and blockchain scalability for multi-party transaction. Last, the paper is summarized and future research directions are proposed.

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Permissioned Blockchain-Based Anonymous and Traceable Aggregate Signature Scheme for Industrial Internet of Things

Cited by 32 publications

References 40 publications

Blockchain-Based Robust Data Security Scheme in IoT-Enabled Smart Home

Blockchain-Based Robust Data Security Scheme in IoT-Enabled Smart Home

Enhanced Elman spike neural network fostered blockchain framework espoused intrusion detection for securing Internet of Things network

A Quantum Blind Multi-Signature Method for the Industrial Blockchain

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