ABSTRACT: Privacy-Preserving Content-based image retrieval (CBIR) applications have been rapidly developed along with the increase in the quantity, availability and importance of images in our daily life. However, the wide deployment of the CBIR scheme has been limited by its severe computation and storage requirements. In a privacy- preserving content-based image retrieval scheme, it allows the data owner to outsource the image database and CBIR service to the cloud, without revealing the actual content of the database to the cloud server. Local features are utilized to represent the images, and earth mover’s distance (EMD) is employed to evaluate the similarity of images. The EMD computation is essentially a linear programming (LP) problem. The proposed scheme transforms the END problem in such a way that the cloud server can solve it without learning the sensitive information. In Addition, local sensitive hash (LSH) is utilized to improve the search efficiency. The Security analysis and experiments show the security and efficiency of the proposed scheme. In that the encrypted database, secure searchable index and encrypted query will not reveal extra information to the cloud.
Keywords: AES, Advanced Encryption Standard, CBIR, Content-Based Image Retrieval
| DOI: 10.17148/IJARCCE.2021.10742