A Multi-Client Secure Cloud Framework with Enhanced Storage Efficiency and Latency Reduction

  • Unique Paper ID: 175790
  • Volume: 11
  • Issue: 11
  • PageNo: 5036-5038
  • Abstract:
  • Cloud servers provide storage and computational resources at lower costs but face challenges regarding data security and efficiency. This project employs a multi-client Distributed Point Function (DPF)-based keyword search scheme with algorithms like Garbled Bloom Filter and Cuckoo Hash to address these challenges. The segmentation technique optimizes search latency, while Wegman authentication ensures data integrity. To enhance storage efficiency, a data compression algorithm is introduced, and to reduce repeated computation, a caching mechanism is implemented for encrypted search results. These extensions significantly minimize latency, computational costs, and storage requirements, enabling secure and efficient cloud-based keyword searches. The proposed system demonstrates a comprehensive solution for secure cloud storage with real-world applicability.

Copyright & License

Copyright © 2025 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.

BibTeX

@article{175790,
        author = {Kothakota Yatheesh and T. RajyaLakshmi},
        title = {A Multi-Client Secure Cloud Framework with Enhanced Storage Efficiency and Latency Reduction},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {5036-5038},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175790},
        abstract = {Cloud servers provide storage and computational resources at lower costs but face challenges regarding data security and efficiency. This project employs a multi-client Distributed Point Function (DPF)-based keyword search scheme with algorithms like Garbled Bloom Filter and Cuckoo Hash to address these challenges. The segmentation technique optimizes search latency, while Wegman authentication ensures data integrity. To enhance storage efficiency, a data compression algorithm is introduced, and to reduce repeated computation, a caching mechanism is implemented for encrypted search results. These extensions significantly minimize latency, computational costs, and storage requirements, enabling secure and efficient cloud-based keyword searches. The proposed system demonstrates a comprehensive solution for secure cloud storage with real-world applicability.},
        keywords = {Cloud computing, Distributed Point Function (DPF), Keyword search, Garbled Bloom Filter, Cuckoo Hash, Segmentation technique, Wegman authentication, Data integrity, Data compression algorithm.},
        month = {April},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 11
  • PageNo: 5036-5038

A Multi-Client Secure Cloud Framework with Enhanced Storage Efficiency and Latency Reduction

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