A Privacy-Preserving Content-Based Image Retrieval Method

Now days, Cloud computing it is been playing a crucial role in terms of data storing and reducing the overall cost to entrepreneurs. Storage requirements for visual data have increased in recent years, following the appearance of many interactive multimedia services and applications for mobile devices in personal and business scenarios. This was a key a determining factor for the adoption of cloud-based data outsourcing solutions. However, even the outsourcing of data storage in the cloud leads to new security challenges that must be carefully addressed. We propose a secure framework for the storage and recovery of the subcontracted privacy protection in large archives of shared images. Our proposal is based on IES-CBIR, a novel Encryption scheme of the image that presents image recovery properties based on content. The framework allows both encrypted storage and search using content-based image retrieval queries while preserving privacy against honest but curious cloud administrators. We have built a prototype of the proposed framework, formally analyzed and tested its safety properties, and experimentally assessed its performance and accuracy of recovery.