Personal identifiable information privacy model for securing of users’ attributes transmitted to a federated cloud environment
| Autor: | Afolayan A. Obiniyi, Maria Abur, Sahalu B. Junaidu |
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| Rok vydání: | 2021 |
| Předmět: |
Computer Networks and Communications
business.industry Computer science Applied Mathematics Privacy policy Advanced Encryption Standard Cryptography Cloud computing Computer security computer.software_genre Encryption Identity management Computer Science Applications Computational Theory and Mathematics Artificial Intelligence Federated identity Electrical and Electronic Engineering business Personally identifiable information computer Information Systems |
| Zdroj: | International Journal of Information Technology. 14:421-435 |
| ISSN: | 2511-2112 2511-2104 |
| Popis: | One of the security issues affecting Federated Cloud Environment users is privacy. It is the ability to secure and control the Personal Identifiable Information (PII) of a user during and after being communicated to the Cloud. Existing studies addressed the problem using techniques such as: uApprove, uApprove.jp, enhanced privacy and dynamic federation in Identity Management (IdM), privacy-preserving authorization system, end-to-end Privacy Policy Enforcement in Cloud Infrastructure, multi-tenancy authorization system with federated identity, and a Cryptography Encryption Key and Template Data Dissemination (CEKTTDD). Users’ PIIremains vulnerable as existing researches lack efficient control of user's attributes in the Cloud. This paper proposes a PIIPrivacy model for protecting user’s attributes on transit to the Federated Cloud Environment. The approach used, combined Advanced Encryption Standard (AES 128) and Discrete Cosine Transform Modulus three (DCTM3) steganography to improve CEKTTDD technique. This was achieved by techniques to encrypt user’s PIIs. The model was implemented using Matrix Laboratory (MATLAB) and evaluated using undetectability, robustness, match (%), encryption time and decryption time. Chi-square attack was applied to prove the security of the proposed model. Results obtained showed that the proposed model was stronger in robustness with values of ((59.10 dB) and (55.45 dB) than the existing model of values ((55.76 dB) and (54.15 dB)). Similarly, the proposed system successfully minimizes undetectability than the former model, while evaluation for match (%) yielded 17% increase better than the existing system. This study has achieved a state-of-the-art model for a secured user’s attributes in the cloud. |
| Databáze: | OpenAIRE |
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