Blockchain-Enabled Secure Data Sharing with Honey Encryption and DSNN-Based Key Generation

Reshma Siyal, Jun Long, Muhammad Asim (), Naveed Ahmad, Hanaa Fathi and Mohammad Alshinwan
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Reshma Siyal: School of Computer Science and Engineering, Central South University, Changsha 410083, China
Jun Long: School of Computer Science and Engineering, Central South University, Changsha 410083, China
Muhammad Asim: EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
Naveed Ahmad: EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
Hanaa Fathi: Applied Science Research Center, Applied Science Private University, Amman 11931, Jordan
Mohammad Alshinwan: Faculty of Information Technology, Applied Science Private University, Amman 11931, Jordan

Mathematics, 2024, vol. 12, issue 13, 1-25

Abstract: Ensuring data confidentiality is a critical requirement for modern security systems globally. Despite the implementation of various access-control policies to enhance system security, significant threats persist due to insecure and inadequate access management. To address this, Multi-Party Authorization (MPA) systems employ multiple authorities for authorization and authentication, utilizing blockchain technology to store and access data securely, ensuring immutable and trusted audit trails. In this work, we propose a hybrid key-generation approach called the Identity and Attribute-Based Honey Encryption (IABHE) Algorithm combined with Deep Spiking Neural Network (DSNN) denoted by IABHE+DSNN for secure data sharing in a multi-party blockchain-based system. This approach incorporates various entities and multiple security functionalities to ensure data security. The data-sharing process involves several steps: initialization, authentication, initial registration, data protection, validation, and data sharing. Data protection is executed within the MapReduce framework, with data encryption performed using IABHE and key generation managed by DSNN. Experimental results demonstrate that the proposed IABHE+DSNN approach achieves a decryption time of 10.786 s, an encryption time of 15.765 s, and a key complexity of 0.887, outperforming existing methods.

Keywords: blockchain; authentication; identity-based encryption; deep spiking neural network; honey encryption algorithm; attribute-based encryption; data security (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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