# Separable Data-Hiding Scheme for Encrypted Image to Protect Privacy of User in Cloud
## 1 Introduction
's scheme [19] introduced random diffusion and an accurate prediction strategy to efficiently use the correlation of pixels in order to obtain greater hiding capacity. By compressing the encrypted LSBs, [PERSON]'s scheme [20] made space for data hiding in order to separate the extraction of data from image decryption. This separable data-hiding scheme provides more flexibility in protecting the privacy of users' data. The receiver can extract the hidden data or decrypt/reconstruct the protected private image, respectively, according to the key he/she permits. Figure 1 shows the three different cases for the receiver, i.e., (1) If a receiver has only the data-hiding key, he/she can extract the hidden data without seeing the content of the image; (2) If a receiver has only the encryption key, he/she can decrypt or reconstruct the protected private image, which is similar to the original image, but cannot extract the hidden data; (3) If the receiver has both the encryption key and the data-hiding key, he/she can extract the hidden data and reconstruct the protected private image. Most of the existing separable data-hiding schemes for encrypted images (SDH-EI) hide data in the spatial domain [20; 21; 22], which makes them sensitive to the loss of data, and the protected image and the hidden data cannot be recovered if the encrypted image that contains the hidden data is damaged. Also, the hiding capacity is quite low. However, the separable data-hiding schemes for encrypted images based on compressive sensing (SDH-EI-CS) [23; 24; 25] inherited the performance of compressive sensing (CS) and overcame the disadvantages of lost data and low capacity. In 2014, [PERSON] and [PERSON] [23] proposed a novel SDH-EI-CS scheme in which the protected image was encrypted with an encryption key and some extra space was made available to hide data. Then, the enlarged stego-image was compressed to the original size by compressive sensing (CS). Compared with the previous schemes, this scheme included the separable idea in [20], and achieved good performance of anti-data-loss. However, it did not have the compression property, and the hidden data had a small loss due to compression sensing. Later, [PERSON] et al. [24] improved the performance of this scheme by using the block discrete cosine transform (DCT) and obtained the merits of being able to compress the ciphertext. But the quality of the directly recovered image was decreased. In 2017, [PERSON] et al. [25] presented as SDH-EI-CS scheme based on the discrete fourier transform (DFT) to achieve a better quality of the directly decrypted images, but with the compressibility of the cipher text sacrificed. In this paper, we propose a new scheme of separable data hiding in encrypted images based on block compressive sensing (SDH-EI-BCS). This scheme fully includes the features of flexible compression and anti-data-loss in block compressive sensing (BCS), and its design provides a simple method of data hiding that is easy to implement as well as separate reconstruction and extraction approaches. Compared with the previous work of SDH-EI-CS, our proposed scheme reduces the complexity of the scheme and achieves better performance in compression, anti-data-loss and hiding capacity. So, the proposed scheme provides a convenient and secure approach for processing, storing and transmitting users' data in cloud computing. The rest of this paper is organized as follows. Section 2 briefly describes three related works about block compressive sensing. In Section 3, we describe the proposed scheme. Section 4 presents the experimental results of the proposed scheme, and our conclusions are stated in Section 5.