Blockchain based handle system to secure Predictive maintenance analysis system in Industrial IoT using L2S–GRU

Abstract

The handle system that assigns persistent identifiers to the information resources is utilized by the Predictive Maintenance analysis. The persistent identifiers are referred to as the handles that assist as a unique and enduring reference for locating, accessing, and utilizing the resources. Nevertheless, Industrial Internet of Things devices were affected by insider attacks in most of the prevailing works. Thus, an effective Blockchain-enabled secure handle system using Adversarial Stylometry-KAnonymity and $Lo{g}^2$ Sigmoid–Gated Recurrent Unit is presented in this paper. It is proposed to enhance the Handle System’s scalability and support real-time data processing. Primarily, the Industrial Internet of Things device and user are registered with the Blockchain. Then, based on Adversarial Stylometry-KAnonymity, the details are privacy preserved. Meanwhile, for the Industrial Internet of Things devices and users, the keys, Quick Response code, and hashcode are generated. Later, the Industrial Internet of Things device setup grounded on Message Authentication Code creation and data sensing is conducted. After that, by using Triangular and S-shaped-fuzzy, a controlled access-based smart contract is created. The Fuzzy system is used to enhance the smart contract by enabling flexible and dynamic decision-making in the context of undefined or inaccurate data. Extensive experiments and analysis proved the effectiveness of the proposed framework for predictive maintenance in Industrial Internet of Things. The outcomes proved that a higher accuracy of 99.12%, Precision of 99.24% and of Recall 99.33% was attained by the proposed model, thereby outperforming similar existing models.