Feature Extraction using SIFT for Privacy Preserving Over Encrypted Image

Authors(2) :-Pranjali M Marne, Prof. P. M. Kamde

In past a huge number of the data owners stores their individual multimedia information so for the communication to be carried out securely, the private information shouldn’t be reveal by its originated application of the owners as it does outsourced multimedia. Thus it is important to maintain the privacy by preserving the computation in outsource multimedia data. Thus the privacy-preservation will be implemented using SIFT (Scale Invariant Feature Transform) algorithm over the image. The data set owner is responsible to have the image data set thus which is responsible to send the image to server thus the feature extraction is done by using SIFT. The Batched Secure Multiplication Protocol for the communication between the servers and Batched Secure Comparison protocol for the comparison. It uses somewhat holomorphic encryption technique. TheCaltech256 standard dataset is used and the application users will have high level of security on image data.

Authors and Affiliations

Pranjali M Marne
Department of Computer Engineering, Sinhgad College of Engineering, Savitribai Phule, Pune University, Pune, Maharashtra, India
Prof. P. M. Kamde
Department of Computer Engineering, Sinhgad College of Engineering, Pune, Savitribai Phule, Pune University, Pune, Maharashtra, India

SIFT, Encryption, Feature Selection, Secure Data Outsourcing.

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Publication Details

Published in : Volume 4 | Issue 8 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 664-669
Manuscript Number : IJSRSET1184472
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Pranjali M Marne, Prof. P. M. Kamde, " Feature Extraction using SIFT for Privacy Preserving Over Encrypted Image, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 8, pp.664-669, May-June-2018.
Journal URL : http://ijsrset.com/IJSRSET1184472

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