Transfer Fuzzy Learning enabled Streebog Cryptographic Substitution Permutation based zero trust security in IIOT

Abstract

The advent of the fourth industrial revolution and connection with devices and sensors produced extensive arbitrary, discordant data in IIoT platforms. The IIoT platforms have experienced a sea change and their progressively difficult and acquiring intricate. As a result, devices within the network manifest part of the trusted network, therefore compromising other devices in the network. In order to, circumvent is a requirement for a simple safety mechanism between devices to derived by applying a Zerotrust principle. In this work a novel method called, Streebog Cryptographic Substitution Permutation Network-based Transfer Fuzzy Learning (SCSPN-TFL) to improve the network access time. First, device security is designed via the policy engine and policy administrator module using the SCSPN model. SCSPN is performed into IIoT to improve the secure data communication between devices. Next, the device block is sent to receiver for performing decryption and obtaining original device information by such policy and studying communication patterns between devices. Next, data security is presented via a policy enforcement module using Transfer Fuzzy Learning. The results show that the proposed method achieves better data confidentially rate as 8 %, minimal network access time as 28 %, a better data integrity rate as 9 % and a reduced false positive rate as 25 %, as compared to existing techniques.

Keywords

• Zero trust
• Streebog Cryptographic
• Substitution
• Permutation
• Transfer Fuzzy Learning