TY  - JOUR
VL  - 15
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130814564&doi=10.1007%2fs12652-022-03889-8&partnerID=40&md5=6248d9e86ad8f9817a53cdcd5c92471c
JF  - Journal of Ambient Intelligence and Humanized Computing
A1  - Singh, N.
A1  - Kumar, J.
A1  - Singh, A.K.
A1  - Mohan, A.
Y1  - 2024///
KW  - Cloud computing
KW  -  Cloud environments; Cloud-computing; Data outsourcing; Data retrieval; Encrypted data; Fuzzy searches; Hybrid search; Multi keywords; Multi-keyword ranking; Privacy preserving
KW  -  Privacy-preserving techniques
ID  - scholars20299
N2  - Data outsourcing to the cloud is gaining popularity day by day in cloud computing. It requires a dynamic architecture that avoids loopholes and stops intruders from entering the cloud environment. To retrieve the enciphered documents from the cloud, the latest technique that is enrolled effectively is multi-keyword fuzzy search. The proposed research work uses this technique along with the n-gram corpus algorithm that helps to achieve relevancy score and sub-linear search time. This algorithmic combination is able to predict the privacy ranking measure of the retrieved data. To validate the opposed approach, simulation analysis has been performed to preserve user-oriented privacy in a cloud environment. The ranking precision of the proposed method is compared with (Fu et al. in IEEE Trans Inf Forensics Secur 12(8):1874â??1884. https://doi.org/10.1109/TIFS.2017.2692728, 2017) which uses a stemming algorithm and a matching algorithm based on the inner product. The results express the efficiency of the proposed approach by showing a relative improvement in security precision up to 55. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.
IS  - 1
EP  - 274
SN  - 18685137
PB  - Springer Science and Business Media Deutschland GmbH
SP  - 261
TI  - Privacy-preserving multi-keyword hybrid search over encrypted data in cloud
N1  - cited By 2
AV  - none
ER  -