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@article{191734,
        author = {Janhvi Mishra},
        title = {Privacy-Preserving Computation Using Homomorphic Encryption in Cloud Computing},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {81-83},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191734},
        abstract = {Cloud computing has evolved into a key technology supporting modern data-driven systems by offering scalable, flexible, and accessible computational resources. However, delegating sensitive data storage and processing to cloud providers introduces significant privacy concerns, particularly regarding unauthorized access and data exposure. Conventional encryption protects stored and transmitted data, but it requires decryption prior to processing, thereby exposing the plaintext during computation. Homomorphic Encryption (HE) overcomes this limitation by enabling operations to be performed directly on encrypted information without revealing the underlying content.
This paper provides an accessible and structured overview of privacy-preserving computation using HE in cloud environments. It covers the theoretical basis of HE, reviews present HE schemes, and examines their practical viability. A prototype implemented using Microsoft SEAL highlights the advantages, constraints, and performance impact of HE. The paper concludes with optimization approaches and discusses future prospects for real-world adoption.},
        keywords = {Cloud Computing, Cryptography, Data Security, Homomorphic Encryption, Privacy Preservation},
        month = {},
        }