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Efficient Cloud Computing Security Using Hybrid Optimized AES-IQCP-ABE Cryptography Algorithm

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Názov: Efficient Cloud Computing Security Using Hybrid Optimized AES-IQCP-ABE Cryptography Algorithm
Autori: Jayaprakash Jayachandran, Dahlia Sam, Kanya Nataraj
Zdroj: International Journal of Computer Network and Information Security. 17:101-114
Informácie o vydavateľovi: MECS Publisher, 2025.
Rok vydania: 2025
Popis: Data management has been revolutionized because cloud computing technologies have increased user barriers to expensive infrastructure and storage limits. The advantages of the cloud have made it possible for significant cloud implementation in major businesses. However, the privacy of cloud-based data remains the significant and most crucial problem for data owners due to various security risks. Many researchers have proposed various methods to maintain the confidentiality of the data, including attribute-based encryption (ABE). Though, the cloud is still dogged mainly by the security issue. To protect data privacy, the new encryption model "Advanced Encryption Standard- Improved Quantum Ciphertext Policy and Attribute-based Encryption" (AES-IQCP-ABE) is introduced in the present research. The suggested method twice encrypts the data and the attributes using the ABE at first. Second, using the AES technique, the encrypted data is encrypted before being delivered to authorized users. The dynamic, chaotic map function is used in the proposed approach to protecting user attributes throughout the initialization of the key, encryption of data, and decryption of data processes. For the encryption process, the inputs used in the proposed research are both unstructured and structured extensive medical data. Regarding computational memory, time for cloud data encryption, and decryption, the proposed model outperforms the previous ABE-based encryption and decryption algorithms.
Druh dokumentu: Article
ISSN: 2074-9104
2074-9090
DOI: 10.5815/ijcnis.2025.02.07
Prístupové číslo: edsair.doi...........099a4f41b9ae07af7881ce180e80cf0e
Databáza: OpenAIRE
Popis
Abstrakt:Data management has been revolutionized because cloud computing technologies have increased user barriers to expensive infrastructure and storage limits. The advantages of the cloud have made it possible for significant cloud implementation in major businesses. However, the privacy of cloud-based data remains the significant and most crucial problem for data owners due to various security risks. Many researchers have proposed various methods to maintain the confidentiality of the data, including attribute-based encryption (ABE). Though, the cloud is still dogged mainly by the security issue. To protect data privacy, the new encryption model "Advanced Encryption Standard- Improved Quantum Ciphertext Policy and Attribute-based Encryption" (AES-IQCP-ABE) is introduced in the present research. The suggested method twice encrypts the data and the attributes using the ABE at first. Second, using the AES technique, the encrypted data is encrypted before being delivered to authorized users. The dynamic, chaotic map function is used in the proposed approach to protecting user attributes throughout the initialization of the key, encryption of data, and decryption of data processes. For the encryption process, the inputs used in the proposed research are both unstructured and structured extensive medical data. Regarding computational memory, time for cloud data encryption, and decryption, the proposed model outperforms the previous ABE-based encryption and decryption algorithms.
ISSN:20749104
20749090
DOI:10.5815/ijcnis.2025.02.07