Dr.SriSudha Garugu, K. Manideep, P. Pavani Durga, P. Chandhu
Abstract
Cloud computing enables scalable data storage; however, secure and efficient retrieval of encrypted data remains a critical challenge. Traditional searchable encryption techniques either suffer from high computational overhead or lack strong privacy guarantees. To address these limitations, this paper proposes a Dual Server Public Key Encryption with Intelligent Keyword Search (DS-PEKS) framework for secure cloud storage. The proposed model separates query processing across two non-colluding servers, ensuring enhanced privacy and resistance to keyword guessing attacks. Additionally, intelligent keyword search mechanisms improve retrieval accuracy and efficiency. Experimental analysis demonstrates that the proposed system achieves improved security and optimized search performance compared to existing approaches.
Keywords
Cloud Security, Public Key Encryption, Keyword Search, Dual Server Architecture, Data Privacy, Secure Cloud Storage, Searchable Encryption, PEKS, Keyword Guessing Attack.
Conclusion
This system presented a DS-PEKS-based secure cloud storage system that enhances privacy and efficiency in encrypted keyword search. By utilizing dual-server architecture, the proposed model ensures resistance against keyword guessing attacks and reduces data leakage. The integration of intelligent search techniques further improves retrieval accuracy. Future work includes integrating block chain for decentralized trust and optimizing the system using deep learning-based ranking mechanisms.
References
[1]D. Boneh et al., “Public Key Encryption with Keyword Search,” EUROCRYPT, 2004. [2]R. Curtmola et al., “Searchable Symmetric Encryption,” ACM CCS, 2006. [3]N. Cao et al., “Privacy-Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data,” IEEE INFOCOM, 2011. [4]C. Wang et al., “Privacy-Preserving Ranked Keyword Search,” IEEE TPDS, 2021. [5]S. Garugu and S. Narendra, “Security Maintain Group Keyword Search Using Multi-Dimensional Algorithm in Cloud Computing,” IJSETR, 2016. [6]W. Sun et al., “Privacy-Preserving Multi-keyword Text Search,” IEEE INFOCOM, 2013. [7]S. Kamara and K. Lauter, “Cryptographic Cloud Storage,” Financial Cryptography, 2010. [8]S. Garugu and D. L. Bhaskari, “Automatic Information Extraction Using Templates,” JDAP, 2022. [9]R. Bost, “Forward Secure Searchable Encryption,” ACM CCS, 2016. [10]J. Liu et al., “Deep Learning Assisted Secure Search,” IEEE TCC, 2023. [11]S. Garugu et al., “Proactive Network Defense,” IJPREMS, 2025. [12]X. Chen et al., “Federated Learning Based Secure Retrieval,” FGCS, 2024. [13]J. Li et al., “Dual-Server Searchable Encryption,” IEEE TCC, 2019. [14]S. Garugu et al., “Multimodal Content Analysis and Classification Approach,” JES, 2024. [15]Y. Zhang et al., “Blockchain-Based Searchable Encryption,” IEEE Access, 2022. [16]S. Garugu and M. Ramesh, “Innovating Machine Learning in AI,” IJITECH, 2016. [17]S. Garugu and D. L. Bhaskari, “Abstractive Text Summarization,” IJISAE, 2024. [18]D. Cash et al., “Dynamic Searchable Encryption,” NDSS, 2014. [19]S. Garugu et al., “Question Answering using XLM-RoBERTa,” IJRAR, 2023. S. Garugu and D. L. Bhaskari, “Hybrid Neural Machine Translation,” IJRITCC, 2023.
How to Cite This Paper
Dr.SriSudha Garugu, K. Manideep, P. Pavani Durga, P. Chandhu (2026). DUAL SERVER PUBLIC KEY ENCRYPTION WITH INTELLIGENT KEYWORD SEARCH FOR SECURE CLOUD STORAGE. International Journal of Computer Techniques, 13(2). ISSN: 2394-2231.
