Enabling Secure Authentication in Industrial IoT With Transfer Learning Empowered Blockchain

Wang, Xiaoding; Garg, Sahil; Lin, Hui; Piran, Md. Jalil; Hu, Jia; Hossain, M. Shamim

doi:10.1109/tii.2021.3049405

Cited by 53 publications

(46 citation statements)

References 20 publications

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“…In this paper, an efficient mechanism for authentication is formulated that helps in the empowerment of blockchain. It helps construct intelligent and trustworthy blockchains through the creation of multi-tier structures for each of the applications of IoT and creates an internal and outer blockchain structure [ 11 ]. Additionally, the blockchain helps in authenticating and enhancing the usability of local users in several regions.…”

Section: System Modelmentioning

confidence: 99%

“…The users plays a significant role in connecting with the innermost or outermost blockchain if they successfully clear the authentication test [ 11 ]. A user who works efficiently in the

enhances their innermost credit and helps the user clear their authentication of

.…”

Section: System Modelmentioning

confidence: 99%

“…Enriching transfer learning with neural translation deployment was introduced in [ 10 ], where the features of a lexicon were introduced with transfer learning with a shared vocabulary. The author in [ 11 ] proposed the semi-supervised attention model, which helps in discriminating feature embedding, and a high accuracy rate was achieved. The enhanced authentication protocol was introduced in that research [ 12 ], and a new method of authentication and key exchange protocol was discovered to give an efficient authentication mechanism for IoT.…”

Section: Introductionmentioning

confidence: 99%

“…All of the intelligent terminals of industrial applications are responsible for collecting industrial data that is reliable and efficient. The edge server is a component of the edge intelligent network, blockchain system, and artificial intelligence [ 11 ]. They are responsible for analysis, fusion, and processing of the data; for providing security to data; and for protecting its privacy for many IIoT applications.…”

Section: Introductionmentioning

confidence: 99%

“…All of the essential contributions that have been conducted with the help of this paper are highlighted below: The privacy of a user’s various blockchains that have been brought forward to authenticate the mechanism of the users is successfully and efficiently preserved so that it protects them from all attacks [ 11 ]. The blockchains that introduced are the inner as well as the outer blockchains.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT

Arumugam

Maurya

et al. 2021

Sensors

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The Industrial Internet of Things (IIoT) has led to the growth and expansion of various new opportunities in the new Industrial Transformation. There have been notable challenges regarding the security of data and challenges related to privacy when collecting real-time and automatic data while observing applications in the industry. This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. In FT-Block (Federated transfer learning blockchain), several blockchains are applied to preserve privacy and security for all types of industrial applications. Additionally, by introducing the authentication mechanism based on transfer learning, blockchains can enhance the preservation and security standards for industrial applications. Specifically, Novel Supportive Twin Delayed DDPG trains the user model to authenticate specific regions. As it is considered one of the most open and scalable interacting platforms of information, it successfully helps in the positive transfer of different kinds of data between devices in more significant and local operations of the industry. It is mainly due to a single authentication factor, and the poor adaptation to regular increases in the number of users and different requirements that make the current authentication mechanism suffer a lot in IIoT. As a result, it has been very clearly observed that the given solutions are very useful.

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Section: System Modelmentioning

confidence: 99%

“…The users plays a significant role in connecting with the innermost or outermost blockchain if they successfully clear the authentication test [ 11 ]. A user who works efficiently in the

enhances their innermost credit and helps the user clear their authentication of

.…”

Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT

Arumugam

Maurya

et al. 2021

Sensors

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Mobile‐fog‐cloud assisted deep reinforcement learning and blockchain‐enable IoMT system for healthcare workflows

Lakhan

Mohammed

Kozlov

et al. 2021

Trans Emerging Tel Tech

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The Internet of Medical Things (IoMT) is increasingly being used to secure blockchain technology to operate healthcare applications in a distributed network. The applications are mobile and can move from one place to another with different wireless connectivity. However, there are a lot of challenges that are investigated further. For instance, dynamic content values changed during mobile applications during any business goal. The workflow healthcare applications are complex as compared to coarse‐grained and fine‐grained workload in IoMT. In this article, the study analyzed offloading and scheduling problems for healthcare workflows in IoMT fog‐cloud network. Therefore, the study considered the problem as an offloading and scheduling problem formulated deep reinforcement learning as Markov problem. The study devises the novel deep reinforcement learning and blockchain‐enabled system, consisting of multi‐criteria offloading based on deep reinforcement learning policies and blockchain task scheduling with task sequencing and research matching methods for healthcare workloads in the IoMT system. The simulation results suggested strategies that reduced the communication and computation time for each application in the system.

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Blockchain-Based Authentication in IoT Environments: A Survey

Alani

2022

Advances in Information Security

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Enabling Secure Authentication in Industrial IoT With Transfer Learning Empowered Blockchain

Cited by 53 publications

References 20 publications

Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT

Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT

Mobile‐fog‐cloud assisted deep reinforcement learning and blockchain‐enable IoMT system for healthcare workflows

Blockchain-Based Authentication in IoT Environments: A Survey

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