Data Searches Techniques via Public Key Symmetric Encryption

Authors

  • Swetha.V M.Tech Scholar, Department of Computer Science and Engineering, Veerammal College of Engineering, Dindigul, India
  • Sangeetha.K Assistant Professor, Department of Computer Science and Engineering, Veerammal College of Engineering, Dindigul, India

Keywords:

privacy, cloud computing, multi keyword search, encryption

Abstract

As a first step towards making secure cloud data manipulation a reality, this study describes and solves a challenging technique for performing a search for critical keywords for mixed cloud statistics (MRSE). We select the useful notion of "relational coherence" from the various meanings of multiple keywords. Cloud computing has made it easier and more cost-effective for businesses to subcontract a wide range of products and service community clouds. To ensure Sensitive personal information data must remain encapsulated previously being submitted for their work. A search engine must be able to search for a specific term multiple keyword searches and demonstrate a correlation between them measure to effectively satisfy the necessity of retrieving data given the huge number of users of data and records in the cloud. The easy-to-implement MRSE algorithm is our first recommendation to secure a computer of internal objects. Experimentation on real-world datasets shows that the recommended methodologies do not dramatically improve the computational and communication costs involved. The mapping of feedback sessions to pseudo (false) documents is one of our unique optimization strategies for effectively reflecting user information needs. A new metric for measuring the quality of the reconstructed online search results is called average precision (CAP). Real-world data experiments show that the proposed strategies have a negligible impact on computation and transmission. In order to improve the data search service's search experience, we broaden these two approaches to include additional search semantics.

References

Xiaojun Zhang, Yao Tang, Huaxiong Wang, Chunxiang Xu, Yinbin Miao, & Hang Cheng. (2019). Lattice-based Proxy-oriented Identity-based encryption with keyword search for cloud storage. Inf. Sci., 494, 193–207.

Joël Alwen, & Chris Peikert. (2011). Generating shorter bases for hard random lattices. Theory Comput. Syst., 48(3), 535–553.

Rouzbeh Behnia, Muslum Ozgur Ozmen, & Attila Altay Yavuz. (2020). Latticebased public key searchable encryption from experimental perspectives. IEEE Trans. Dependable Secur. Comput., 17(6), 1269–1282.

Mahnaz Noroozi, & Ziba Eslami. (2019). Public key authenticated encryption with keyword search: Revisited. IET Inf. Secur., 13(4), 336–342.

Oded Regev. (2009). On lattices, learning with errors, random linear codes, and cryptography. J. ACM, 56(6).

Xiaojun Zhang, Chunxiang Xu, Huaxiong Wang, Yuan Zhang, & Shixiong Wang. (2021). FS-PEKS: Lattice-based forward secure public-key encryption with keyword search for cloud-assisted industrial internet of things. IEEE Trans. Dependable Secur. Comput., 18(3), 1019–1032.

Published

2022-07-30

How to Cite

Swetha.V, & Sangeetha.K. (2022). Data Searches Techniques via Public Key Symmetric Encryption. Applied Science and Biotechnology Journal for Advanced Research, 1(1), 16–19. Retrieved from https://abjar.vandanapublications.com/index.php/ojs/article/view/4

Issue

Section

Articles