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A smart decentralized identifiable distributed ledger technology‐based blockchain (DIDLT‐BC) model for cloud‐IoT security.

Authors :
Selvarajan, Shitharth
Shankar, Achyut
Uddin, Mueen
Alqahtani, Abdullah Saleh
Al‐Shehari, Taher
Viriyasitavat, Wattana
Source :
Expert Systems. Jan2025, Vol. 42 Issue 1, p1-25. 25p.
Publication Year :
2025

Abstract

The most important and difficult challenge the digital society has recently faced is ensuring data privacy and security in cloud‐based Internet of Things (IoT) technologies. As a result, many researchers believe that the blockchain's Distributed Ledger Technology (DLT) is a good choice for various clever applications. Nevertheless, it encountered constraints and difficulties with elevated computing expenses, temporal demands, operational intricacy, and diminished security. Therefore, the proposed work aims to develop a Decentralized Identifiable Distributed Ledger Technology‐Blockchain (DIDLT‐BC) framework that is intelligent and effective, requiring the least amount of computing complexity to ensure cloud IoT system safety. In this case, the Rabin algorithm produces the digital signature needed to start the transaction. The public and private keys are then created to verify the transactions. The block is then built using the DIDLT model, which includes the block header information, hash code, timestamp, nonce message, and transaction list. The primary purpose of the Blockchain Consent Algorithm (BCA) is to find solutions for numerous unreliable nodes with varying hash values. The novel contribution of this work is to incorporate the operations of Rabin digital data signature generation, DIDLT‐based blockchain construction, and BCA algorithms for ensuring overall data security in IoT networks. With proper digital signature generation, key generation, blockchain construction and validation operations, secured data storage and retrieval are enabled in the cloud‐IoT systems. By using this integrated DIDLT‐BCA model, the security performance of the proposed system is greatly improved with 98% security, less execution time of up to 150 ms, and reduced mining time of up to 0.98 s. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02664720
Volume :
42
Issue :
1
Database :
Academic Search Index
Journal :
Expert Systems
Publication Type :
Academic Journal
Accession number :
181701552
Full Text :
https://doi.org/10.1111/exsy.13544