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Dynamic Multi-Keyword Search for Secure Data Storage in the Cloud using Cuckoo Filter.

Authors :
Rao, Gadu Srinivasa
Ravi, Tanishq
Preetham, Gogineni Venkata Sai
Attada, Jacinth
Pranitha, Bojja
Baikadi, Srikanth Reddy
Chitikala, Sai Joshitha
Rayani, Vignesh
Source :
Journal of Cardiovascular Disease Research (Journal of Cardiovascular Disease Research). 2021, Vol. 12 Issue 4, p741-752. 12p. 5 Diagrams, 1 Chart.
Publication Year :
2021

Abstract

In current days cloud domain gained a tremendous increase of user's attention by several small and large scale companies including Software, BPO, Medical, Schools and a lot more. Since there was very less security in the primitive clouds for storing and accessing the information from the remote locations, still there was a lot of demand for the data which is to be stored in the cloud. As we know that in primitive clouds, there are no concepts like privacy for the data in terms of encryption and message digest in order to provide data authorization. In current days cloud servers are almost dishonest in nature by omitting intentionally some qualified results to save computational resources and communication overhead. In this paper, we try to design a new protocol and analyze the importance of Cuckoo filter over encrypted cloud data to provide data search accurately by the cloud users. Here we try to encrypt the data using AES algorithm and try to generate MAC key for the data which is uploaded and downloaded by the cloud users. For data authorization we use MD5 algorithm and with the help of MD5 algorithm, we can generate a short signature to find out the data verification and finally we try to apply Cuckoo filter for data integrity. This cuckoo filter will try to store the data in duplicated manner and try to provide end user with original data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09753583
Volume :
12
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Cardiovascular Disease Research (Journal of Cardiovascular Disease Research)
Publication Type :
Academic Journal
Accession number :
151994373