A Similarity Search Scheme over Encrypted Cloud Images based on Secure Transformation

With the growing popularity of cloud computing, more and more users outsource their private data to the cloud. To ensure the security of private data, data owners usually encrypt their private data before outsourcing the data to the cloud server, which brings incommodity of data operating. This paper proposes a scheme for similar search on encrypted images. In the setup phase, image owner extracts feature vectors to represent the images as usual image retrieval system does. Then, the feature vectors are transformed by an invertible matrix, which not only protect the information of feature vector but also support similarity evaluation between the vectors. The encrypted vectors and image identifies are used to construct inverted index, which is finally uploaded along with the encrypted image to the cloud. In the search phase, with a query image, the authorized image user extracts and encrypts feature vector to generate the trapdoor. The trapdoor is submitted to the cloud and can be used to calculate the similarity with the transformed feature vectors. The encryption on features does not degrade the result accuracy. Moreover, the image owner could update the encrypted image database as well as the secure index very easily.