OPPR: An Outsourcing Privacy-Preserving JPEG Image Retrieval Scheme with Local Histograms in Cloud Environment

As the wide application of imaging technology, number big image data which may containing private information is growing fast. Due to insufficient computing power and storage space for local server device, many people hand over these images cloud servers management. But actually, it unsafe store cloud, so encryption becomes a necessary step before uploading reduce risk privacy leakage. However, not conducive efficient image, especially in Content-Based Image Retrieval (CBIR) scheme. This paper proposes an outsourcing privacypreserving JPEG CBIR We design set format-compatible method, making no file expansion files. firstly combine multiple adjacent 8 × DCT coefficient blocks into big-blocks. Then, random scrambling stream are used on binary code coefficients protect privacy. The task extracting features from encrypted retrieving similar done by server. group index histograms extracted big-blocks, then global vector produced represent with aid bagof-words (BOW) model. security analysis experimental results show that our proposed scheme has strong good retrieval performance.