Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{179223,
        author = {ALIN HIMA S and JHANSI V K and KOTAPATI VENKATA SESHA SAI HIMAJA and GNANAPRAKASAM C},
        title = {SECURING ENCRYPTED GRAPH ANALYSIS IN THE CLOUD ADVANCES IN PRIVACY-PRESERVING SPECTRAL METHOD},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5901-5905},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179223},
        abstract = {As the adoption of cloud-based solutions accelerates, there is a pressing need for systems that can ensure the secure handling of sensitive data while supporting efficient analytical operations. To address this challenge, we propose a robust framework that facilitates encrypted graph data analysis within a secure cloud infrastructure. The system combines strong privacy protections with operational efficiency by incorporating a layered access control mechanism. User registration is overseen by a dedicated Third Party Authority (TPA), which issues authentication tokens after identity verification. These tokens work alongside unique encryption keys generated by a centralized Key Distribution Center (KDC), ensuring that file access is restricted to authorized individuals only. Users can perform core operations such as uploading, downloading, or revoking access with full confidence in the system's security model.},
        keywords = {Spectral Encryption, TPA (Third Party Authority), KDC (Key Distribution Center), Encrypted Graph Analysis, Token-Based Access Control, File-Level Security, Access Revocation Mechanism, Confidential Data Computation, Cloud Privacy Framework.},
        month = {May},
        }