An Efficient Hybrid QHCP-ABE Model to Improve Cloud Data Integrity and Confidentiality
Cloud computational service is one of the renowned services utilized by employees, employers, and organizations collaboratively. It is accountable for data management and processing through virtual machines and is independent of end users’ system configurations. The usage of cloud systems is very si...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-10-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/11/21/3510 |
| _version_ | 1797468496982966272 |
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| author | Kranthi Kumar Singamaneni Ali Nauman Sapna Juneja Gaurav Dhiman Wattana Viriyasitavat Yasir Hamid Joseph Henry Anajemba |
| author_facet | Kranthi Kumar Singamaneni Ali Nauman Sapna Juneja Gaurav Dhiman Wattana Viriyasitavat Yasir Hamid Joseph Henry Anajemba |
| author_sort | Kranthi Kumar Singamaneni |
| collection | DOAJ |
| description | Cloud computational service is one of the renowned services utilized by employees, employers, and organizations collaboratively. It is accountable for data management and processing through virtual machines and is independent of end users’ system configurations. The usage of cloud systems is very simple and easy to organize. They can easily be integrated into various storages of the cloud and incorporated into almost all available software tools such as Hadoop, Informatica, DataStage, and OBIEE for the purpose of Extraction-Transform-Load (ETL), data processing, data reporting, and other related computations. Because of this low-cost-based cloud computational service model, cloud users can utilize the software and services, the implementation environment, storage, and other on-demand resources with a pay-per-use model. Cloud contributors across this world move all these cloud-based apps, software, and large volumes of data in the form of files and databases into enormous data centers. However, the main challenge is that cloud users cannot have direct control over the data stored at these data centers. They do not even know the integrity, confidentiality, level of security, and privacy of their sensitive data. This exceptional cloud property creates several different security disputes and challenges. To address these security challenges, we propose a novel Quantum Hash-centric Cipher Policy-Attribute-based Encipherment (QH-CPABE) framework to improve the security and privacy of the cloud user’s sensitive data. In our proposed model, we used both structured and unstructured big cloud clinical data as input so that the simulated experimental results conclude that the proposal has precise, resulting in approximately 92% correctness of bit hash change and approximately 96% correctness of chaotic dynamic key production, enciphered and deciphered time as compared with conventional standards from the literature. |
| first_indexed | 2024-03-09T19:08:17Z |
| format | Article |
| id | doaj.art-58d4d55121a946d693e3d94586dabfc7 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T19:08:17Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-58d4d55121a946d693e3d94586dabfc72023-11-24T04:25:04ZengMDPI AGElectronics2079-92922022-10-011121351010.3390/electronics11213510An Efficient Hybrid QHCP-ABE Model to Improve Cloud Data Integrity and ConfidentialityKranthi Kumar Singamaneni0Ali Nauman1Sapna Juneja2Gaurav Dhiman3Wattana Viriyasitavat4Yasir Hamid5Joseph Henry Anajemba6Department of Computer Science and Engineering, School of Technology, GITAM Deemed to be University, Visakhapatnam 530045, IndiaDepartment of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, KoreaDepartment of CS, KIET Group of Institutions, Delhi NCR, Ghaziabad 201206, IndiaDepartment of Electrical and Computer Engineering, Lebanese American University, Beirut 1102 2801, LebanonBusiness Information Technology Division, Department of Statistics, Faculty of Commerce and Accountancy, Chulalongkorn University, Bangkok 10330, ThailandInformation Security and Engineering Technology, Abu Dhabi Polytechnic, Abu Dhabi 111499, United Arab EmiratesInformation Security and Engineering Technology, Abu Dhabi Polytechnic, Abu Dhabi 111499, United Arab EmiratesCloud computational service is one of the renowned services utilized by employees, employers, and organizations collaboratively. It is accountable for data management and processing through virtual machines and is independent of end users’ system configurations. The usage of cloud systems is very simple and easy to organize. They can easily be integrated into various storages of the cloud and incorporated into almost all available software tools such as Hadoop, Informatica, DataStage, and OBIEE for the purpose of Extraction-Transform-Load (ETL), data processing, data reporting, and other related computations. Because of this low-cost-based cloud computational service model, cloud users can utilize the software and services, the implementation environment, storage, and other on-demand resources with a pay-per-use model. Cloud contributors across this world move all these cloud-based apps, software, and large volumes of data in the form of files and databases into enormous data centers. However, the main challenge is that cloud users cannot have direct control over the data stored at these data centers. They do not even know the integrity, confidentiality, level of security, and privacy of their sensitive data. This exceptional cloud property creates several different security disputes and challenges. To address these security challenges, we propose a novel Quantum Hash-centric Cipher Policy-Attribute-based Encipherment (QH-CPABE) framework to improve the security and privacy of the cloud user’s sensitive data. In our proposed model, we used both structured and unstructured big cloud clinical data as input so that the simulated experimental results conclude that the proposal has precise, resulting in approximately 92% correctness of bit hash change and approximately 96% correctness of chaotic dynamic key production, enciphered and deciphered time as compared with conventional standards from the literature.https://www.mdpi.com/2079-9292/11/21/3510cloud modelQH-CPABEprivacysecurity |
| spellingShingle | Kranthi Kumar Singamaneni Ali Nauman Sapna Juneja Gaurav Dhiman Wattana Viriyasitavat Yasir Hamid Joseph Henry Anajemba An Efficient Hybrid QHCP-ABE Model to Improve Cloud Data Integrity and Confidentiality Electronics cloud model QH-CPABE privacy security |
| title | An Efficient Hybrid QHCP-ABE Model to Improve Cloud Data Integrity and Confidentiality |
| title_full | An Efficient Hybrid QHCP-ABE Model to Improve Cloud Data Integrity and Confidentiality |
| title_fullStr | An Efficient Hybrid QHCP-ABE Model to Improve Cloud Data Integrity and Confidentiality |
| title_full_unstemmed | An Efficient Hybrid QHCP-ABE Model to Improve Cloud Data Integrity and Confidentiality |
| title_short | An Efficient Hybrid QHCP-ABE Model to Improve Cloud Data Integrity and Confidentiality |
| title_sort | efficient hybrid qhcp abe model to improve cloud data integrity and confidentiality |
| topic | cloud model QH-CPABE privacy security |
| url | https://www.mdpi.com/2079-9292/11/21/3510 |
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