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Hemnath" }, "sequence": "additional" }, { "role": "publisher", "name": { "org": "Longman Publishers" } } ], "dates": { "published": "2025-03-28", "date_type": "PublicationDate", "online": "2025-03-28" }, "container": { "type": "Journal", "titles": [ { "value": "Journal of Science & Technology", "type": "PrincipalTitle" }, { "value": "J. sci. technol.", "type": "AbbreviatedTitle" } ], "identifiers": [ { "type": "ISSN", "value": "2456-5660", "medium": "electronic" } ], "volume": "10", "issue": "3", "pages": { "first": "20", "last": "27" } }, "links": [ { "url": "https://jst.org.in/index.php/pub/article/view/1211", "return_type": "text/html", "primary": true }, { "url": "https://jst.org.in/index.php/pub/article/download/1211/973", "purpose": "text-mining", "return_type": "application/pdf" } ], "abstract": { "value": "The rapid growth of cloud computing has introduced several challenges regarding the securing of sensitive data.Traditional encryption methods such as those proposed by AES and RSA are unable to efficiently perform withthe scale of large cloud environments as they have high computational cost. Recent advancements that have beenmade in encryption methods, especially concerning homomorphic encryption, appear to unravel an unprecedentedpotential since they provide capabilities for performing computations on encrypted data without the need todecrypt it thus assuring the privacy and integrity of data. However, they are still associated with addingcomputational overhead, and that will definitely pose various challenges for real-time cloud data processing. Thesetup proposed in this paper is a complete framework that integrates homomorphic encryption within a cloudsecurity environment. It evaluates the effectiveness of homomorphic encryption in the cloud for aspects pertainingto performance and security, especially in terms of scalability as well with processing huge amounts of sensitivedata while ensuring much efficiency in performance. Further, the framework includes some prior processing likenormalization so as to optimize efficiency in encryption performance. A comprehensive security analysis isundertaken toward measuring the resistance of such encryption under numerous attack scenarios, and the effectof quantum computing applications on the proposed method of encryption is also discussed in this regard. Thispaper presents a thorough study of performance in conjunction with security trade-offs and, the overalldevelopment of a secure and efficient cloud data processing model." }, "license": { "url": "https://creativecommons.org/licenses/by/4.0", "start": "2025-03-28", "applies_to": "unspecified" }, "references": [ { "key": "ref1", "unstructured": "K. Dondapati, “Lung’s cancer prediction using deep learning,” Int. J. HRM Organ. Behav., vol. 7, no. 1, pp. 1–10, Jan. 2019" }, { "key": "ref2", "doi": "10.1155/2018/8079697", "unstructured": "B. R. Gudivaka, “BIG DATA-DRIVEN SILICON CONTENT PREDICTION IN HOT METAL USING HADOOP IN BLAST FURNACE SMELTING,” Int. J. Inf. Technol. Comput. 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International Journal of Engineering Research and Science & Technology, 16(3), 9-22" } ], "record": { "registrant": "Longman Publishers", "registered": "2025-08-26", "updated": "2026-09-07", "issue_number": 1, "source": "crossref-api", "source_agency": "Crossref (member 25296)" } }, "url_after": "https://jst.org.in/index.php/pub/article/view/1211", "sha256_before": null, "sha256_after": "92f33eedb70421874849ec1abfd59e6d158abe0a99bfa4ffa576a5d1832a6368" }, { "seq": 2, "kind": "update", "at": "2026-09-29 23:59:51", "by": "Administrator (admin)", "by_kind": "user", "note": "record re-read from api.crossref.org", "changes": [ { "path": "container.titles.0.value", "from": "Journal of Science & Technology", "to": "Journal of Science & Technology" } ], "record_after": { "format": "smartscholars-doi-metadata/1.0", "doi": "10.46243/jst.2025.v10.i03.pp20-27", "referent": "Creation", "type": "JournalArticle", "structural_type": "Digital", "modes": [ "Visual" ], "characters": [ "Language" ], "titles": [ { "value": "Fortifying Cloud Security with Advanced Data Encryption Technique", "type": "PrincipalTitle" } ], "identifiers": [ { "type": "DOI", "value": "10.46243/jst.2025.v10.i03.pp20-27" } ], "agents": [ { "role": "author", "name": { "given": "", "family": "Karthikeyan Parthasarathy" }, "sequence": "first" }, { "role": "author", "name": { "given": "", "family": "Naresh Kumar Reddy Panga" }, "sequence": "additional" }, { "role": "author", "name": { "given": "", "family": "Jyothi Bobba" }, "sequence": "additional" }, { "role": "author", "name": { "given": "", "family": "Ramya Lakshmi Bolla" }, "sequence": "additional" }, { "role": "author", "name": { "given": "", "family": "Rajeswaran Ayyadurai" }, "sequence": "additional" }, { "role": "author", "name": { "given": "", "family": "R. Hemnath" }, "sequence": "additional" }, { "role": "publisher", "name": { "org": "Longman Publishers" } } ], "dates": { "published": "2025-03-28", "date_type": "PublicationDate", "online": "2025-03-28" }, "container": { "type": "Journal", "titles": [ { "value": "Journal of Science & Technology", "type": "PrincipalTitle" }, { "value": "J. sci. technol.", "type": "AbbreviatedTitle" } ], "identifiers": [ { "type": "ISSN", "value": "2456-5660", "medium": "electronic" } ], "volume": "10", "issue": "3", "pages": { "first": "20", "last": "27" } }, "links": [ { "url": "https://jst.org.in/index.php/pub/article/view/1211", "return_type": "text/html", "primary": true }, { "url": "https://jst.org.in/index.php/pub/article/download/1211/973", "purpose": "text-mining", "return_type": "application/pdf" } ], "abstract": { "value": "The rapid growth of cloud computing has introduced several challenges regarding the securing of sensitive data.Traditional encryption methods such as those proposed by AES and RSA are unable to efficiently perform withthe scale of large cloud environments as they have high computational cost. Recent advancements that have beenmade in encryption methods, especially concerning homomorphic encryption, appear to unravel an unprecedentedpotential since they provide capabilities for performing computations on encrypted data without the need todecrypt it thus assuring the privacy and integrity of data. However, they are still associated with addingcomputational overhead, and that will definitely pose various challenges for real-time cloud data processing. Thesetup proposed in this paper is a complete framework that integrates homomorphic encryption within a cloudsecurity environment. It evaluates the effectiveness of homomorphic encryption in the cloud for aspects pertainingto performance and security, especially in terms of scalability as well with processing huge amounts of sensitivedata while ensuring much efficiency in performance. Further, the framework includes some prior processing likenormalization so as to optimize efficiency in encryption performance. A comprehensive security analysis isundertaken toward measuring the resistance of such encryption under numerous attack scenarios, and the effectof quantum computing applications on the proposed method of encryption is also discussed in this regard. Thispaper presents a thorough study of performance in conjunction with security trade-offs and, the overalldevelopment of a secure and efficient cloud data processing model." }, "license": { "url": "https://creativecommons.org/licenses/by/4.0", "start": "2025-03-28", "applies_to": "unspecified" }, "references": [ { "key": "ref1", "unstructured": "K. Dondapati, “Lung’s cancer prediction using deep learning,” Int. J. HRM Organ. Behav., vol. 7, no. 1, pp. 1–10, Jan. 2019" }, { "key": "ref2", "doi": "10.1155/2018/8079697", "unstructured": "B. R. Gudivaka, “BIG DATA-DRIVEN SILICON CONTENT PREDICTION IN HOT METAL USING HADOOP IN BLAST FURNACE SMELTING,” Int. J. Inf. Technol. Comput. 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