.png){kind=icon}
.png){kind=icon}
Return
Decentralized Identity Management in Cloud Computing: A Blockchain-Based Solution With Automatic Provisioning Techniques
.png){kind=icon}
OA
AI
DOI：10.1155/int/2969737.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Identity management (IDM) systems in cloud computing struggle to securely manage user identities and access privileges in distributed environments. However, centralized IDM solutions come with high trust costs, single points of failure, and a need for appropriate security response. This paper proposes a novel decentralized IDM framework utilizing blockchain technology and automatic provisioning (AP) techniques to improve cloud computing’s security, scalability, and operational efficiency. The framework employs Ethereum smart contracts and role-based access control (RBAC) to ensure secure, transparent, and automated management of user identities. Key features include support for single sign-on (SSO), multifactor authentication (MFA), and delegated proof-of-stake (DPoS) consensus for secure transaction validation. Our proposed scheme utilizes the Ethereum blockchain and smart contracts for managing user access, ensuring transparent and immutable record-keeping. The scheme introduces RBAC mechanisms to ensure precise privilege allocation and dynamic updates. The scheme also supports key IDM processes, including SSO, MFA, and lifecycle management of identities. The framework incorporates DPoS consensus to enhance security for efficient transaction validation and the prevention of fraud. To address fraudulent activities, the scheme uses machine learning to detect blockchain fraud with 99.1% accuracy, demonstrating robustness and efficiency for large-scale cloud infrastructures.
Keywords:
automatic provisioning
cloud computing
delegated proof-of-stake
Ethereum blockchain
identity management
machine learning
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.7
Papers:
3.0K
Citations:
8.1K