ISSN (Online) :

 Special Issue on The Sustainable Development Goals

Notice Board

Call For Paper:

Volume 9 , March,

Issue 3

Paper 

Submission  

Deadline:

31 March 2025

Vol. 9,  Special Issue (Bi-yearly)



OAIJSE Menu
Imp Links for Reviewer
Invites Proposal for

Enhancing Digital Security with eVault: A Blockchain and AI-Based Storage System 

Abstract

The exponential growth of digital data has necessitated robust, secure, and scalable storage solutions to ensure data integrity and privacy. Conventional cloud storage systems provide accessibility but often fall short in security measures, exposing sensitive information to breaches and unauthorized access. eVault is a next-generation cloud-based digital storage solution designed to address these challenges by incorporating advanced encryption, access control mechanisms, and real-time anomaly detection. This paper presents an in-depth exploration of eVault’s architecture, emphasizing its security framework, performance benchmarks, and comparative analysis with existing storage platforms.The implementation of AES-256 encryption, multi-factor authentication (MFA), and a decentralized key management system ensures data security while maintaining high accessibility and minimal latency. eVault also integrates blockchain technology to enhance data immutability, providing users with a verifiable and tamper-proof audit trail. In addition, role-based access control (RBAC) is implemented to restrict unauthorized access, ensuring that only designated users can retrieve and modify sensitive data.Performance evaluations demonstrate that eVault outperforms traditional storage methods in terms of security resilience, retrieval efficiency, and scalability. The encryption and decryption processes are optimized to minimize computational overhead, making the system suitable for both individual and enterprise-level applications. Furthermore, eVault’s distributed architecture ensures redundancy and high availability, reducing the risk of data loss due to hardware failures.Future advancements in eVault will focus on integrating AI-driven threat detection and optimizing storage efficiency for large-scale enterprise applications. The use of machine learning models to detect anomalies and potential cyber threats in real-time will further enhance eVault’s security framework. Additionally, research will be conducted to explore hybrid encryption models that balance security with computational efficiency, making eVault an even more viable solution for secure digital storage. 

Full Text PDF
Impact Factor
Downloads
NEWS and Updates

Peer Review Process

 ICCEME -2024 conference     

Computer Science ,Electronics, Electrical  Engineering Information Technology, Civil, Computer Science and Engineering , Mechanical, Mechanical-Sandwich Petroleum, Production Instrumentation & Control, Automobile ,Chemical, Electronics Instrumentation& Control, Electronics & Telecommunication  Submit paper at oaijse@gmail.com



Open Access License Policy

Abstracted and Indexed In