Abstract
Advances in cloud computing have aroused many researchers’ interest in privacy-preserving feature extraction over outsourced multimedia data, especially private image data. Since block truncation coding (BTC) is known as a simple and efficient technology for image compression, this paper focuses on privacy-preserving feature extraction in BTC compressed domain. We propose a privacy-preserving computation of BTC feature extraction over massive encrypted images (also called PPBTC). First, all images are uploaded to the cloud after encryption. The privacy-preserving image encryption process consists of block permutation, pixel diffusion, and a bit-plane random shift. BTC features remain unchanged after encryption and the cloud server can directly extract BTC features from the encrypted images. Some analyses and experimental results demonstrate that the proposed privacy-preserving feature extraction scheme for BTC-compressed images is efficient and secure, and it can be applied to secure image computation applications in cloud computing.
Highlights
Nowadays, as one of the most popular multimedia contents, digital images are playing more and more roles in almost every aspect of people’s daily life
Privacy-preserving information retrieval, or searchable encryption are a promising solution to privacy protection in outsourcing data management [1]–[7]
In the cloud computing era, privacy-preserving image computing and searchable encryption are playing an important role in online multimedia data management [8]–[12]
Summary
As one of the most popular multimedia contents, digital images are playing more and more roles in almost every aspect of people’s daily life. Privacy-preserving information retrieval, or searchable encryption are a promising solution to privacy protection in outsourcing data management [1]–[7]. In these schemes, to protect data privacy, sensitive user data will be encrypted before outsourcing to the cloud server. In the cloud computing era, privacy-preserving image computing and searchable encryption are playing an important role in online multimedia data management [8]–[12]. Considering the simplicity and low computation cost of block truncation coding (BTC), we propose a privacy-preserving BTC feature extraction method to ensure the secure sharing of compressed images in the cloud server in this paper.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
