Design and Implementation of an Attribute-Based Encryption to Enhance Privacy in Federated Identity Management (FIM) Systems for Cloud Computing

With the increasing adoption of cloud-based services and distributed systems, securing user identity and sensitive data in Federated Identity Management (FIM) systems has become a critical challenge. Traditional authentication and authorization mechanisms often fall short in ensuring fine-grained access control, especially when dealing with large-scale, dynamic environments. This study explores the enhancement of security in Federated Identity Management (FIM) systems through the integration of Attribute-Based Encryption (ABE), a promising cryptographic technique that offers advanced access control based on user attributes rather than single user identity. The proposed model utilizes Ciphertext-Policy ABE (CP-ABE) to ensure dynamic encryption of user data while also ensuing that only users with the appropriate matching attributes can decrypt and access specific information. By deploying Attribute-Based Encryption, the system enhances privacy, reduces the risk of unauthorized access, and addresses common vulnerabilities in federated systems, such as credential theft and unauthorized privilege escalation. Through a series of experiments, this study evaluates the feasibility and effectiveness of the proposed system in real- world scenarios. The findings suggest that integrating Attribute-Based Encryption into Federated Identity Management systems significantly strengthens security, provides more flexible and granular access control, and mitigates risks associated with traditional identity management approaches. This work will contribute to the field by offering a novel approach to securing federated identity systems in dynamic and complex environments, with implications for both academia and industry in cloud computing, cybersecurity, and privacy-preserving technologies.

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Publication Details

Published
2025-04-09
DOI
https://doi.org/10.38124/ijisrt/25mar657
Primary Topic
Cryptography and Data Security
Type
article
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article

Design and Implementation of an Attribute-Based Encryption to Enhance Privacy in Federated Identity Management (FIM) Systems for Cloud Computing

Andrews Ocran
Cryptography and Data Security
article

Design and Implementation of an Attribute-Based Encryption to Enhance Privacy in Federated Identity Management (FIM) Systems for Cloud Computing

Andrews Ocran
article en

Abstract

With the increasing adoption of cloud-based services and distributed systems, securing user identity and sensitive data in Federated Identity Management (FIM) systems has become a critical challenge. Traditional authentication and authorization mechanisms often fall short in ensuring fine-grained access control, especially when dealing with large-scale, dynamic environments. This study explores the enhancement of security in Federated Identity Management (FIM) systems through the integration of Attribute-Based Encryption (ABE), a promising cryptographic technique that offers advanced access control based on user attributes rather than single user identity. The proposed model utilizes Ciphertext-Policy ABE (CP-ABE) to ensure dynamic encryption of user data while also ensuing that only users with the appropriate matching attributes can decrypt and access specific information. By deploying Attribute-Based Encryption, the system enhances privacy, reduces the risk of unauthorized access, and addresses common vulnerabilities in federated systems, such as credential theft and unauthorized privilege escalation. Through a series of experiments, this study evaluates the feasibility and effectiveness of the proposed system in real- world scenarios. The findings suggest that integrating Attribute-Based Encryption into Federated Identity Management systems significantly strengthens security, provides more flexible and granular access control, and mitigates risks associated with traditional identity management approaches. This work will contribute to the field by offering a novel approach to securing federated identity systems in dynamic and complex environments, with implications for both academia and industry in cloud computing, cybersecurity, and privacy-preserving technologies.

Openalex Percentile: Top 97%
Cryptography and Data Security
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