Image Feature Extraction in Encrypted Domain With Privacy-Preserving SIFT

234 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion (2019, background): “Though some efforts tried to apply encryption algorithms [115-118] to achieve privacy preservation in extracting features from images, the timeliness requirement in smart transportation makes it inappropriate to apply encryption and seriously obfuscates this issue.”
An Efficient MSB Prediction-Based Method for High-Capacity Reversible Data Hiding in Encrypted Images (2018, background): “Many applications exist, such as visual secret sharing (VSS) [3], [14], research and indexing in encrypted databases [7], [11] or recompression of crypto-compressed images [8].”
Surf feature extraction in encrypted domain (2014, background): “In [6], an image feature extraction in the encrypted domain with privacy-preserving SIFT (Scale-invariant feature transform) feature has been proposed, which works directly on the encrypted image.”
Secure Multilayer Perceptron Based On Homomorphic Encryption (2018, background): “Diﬀerent solutions have been proposed so as to securely compare encrypted data [5,12,15,22].”