A trusted computing framework for cloud data security using role-based access and pattern recognition

doi:10.1007/s10586-024-04274-0

2024-03-05

PRE

G. K. Pradhan

Madhukrishna Priyadarsini *

DOI：10.1007/s10586-024-04274-0

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摘要

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Due to the digitization of data and the dynamic requirements of the users, cloud computing is one of the most used technologies in the present scenario. Cloud computing provides a platform to store, process, and share data remotely for heterogeneous users and provides services according to the requests generated by those users. However, its rapid growth has led to one of the major challenges in the environment; the security and privacy of the data. To address the security and privacy concerns, in this paper, our major contribution is a trusted computing framework namely Secure Framework using Behavior and Role Analysis (SFBRA) for cloud data security. The framework utilizes user log monitoring data, pattern recognition algorithms, and role-based access mechanisms to detect malicious and suspicious activities of different users. Our proposed framework provides two levels of security for cloud users. In Level-1, we calculate the trust value of the logged-in users by analyzing the existing log table and pattern of request access. In Level-2, we calculate the trust of the request (storage, processing, sharing) data packet using behavior analysis of the user and a role-based access mechanism and finally detect the malicious activities. The efficacy of our proposed framework is demonstrated through experimentation, where we compare our framework with existing research works. The results show 95% accuracy in potential attack detection and prevention,approximately 8 Mbps throughput, and 0.003% packet drop on average.

Keyword:

Cloud computing

Security

Attack detection

Behavior analysis

Role-based access

Pattern recognition

Trust calculation