# Automatic Selective Encryption of DICOM Images
## 1 Introduction and Related Work
### Related Work  
Many research works focus on the nature of the DICOM image data before and after the encryption, while ignoring the real-time requirements. Hence, encrypting large DICOM images using Naive approach have a large processing time overhead. In the literature, many research works have proposed the use of a selective encryption approach to overcome the processing time limitations for multimedia data. However, fewer numbers of research works have been conducted on the use of selective encryption on medical images, specifically DICOM images. The basic idea of selective encryption is to encrypt the informative subsets of the data using a robust encryption algorithm while encrypting other subsets using a lighter encryption algorithm. Further, the selection and encryption processes of data subsets can be performed in the frequency or spatial domain. Furthermore, the selective approach has a better processing time than the Naive approach, but on the other hand, the Naive approach is considered to be more robust. Most of the utilized image encryption techniques for medical applications in the literature are chaotic-based Naive encryption, while a small number of research works have presented conventional-based image encryption approaches. Additionally, a smaller number of research works have proposed the use of both conventional and chaotic-based approaches (hybrid). Moreover, most of the presented encryption research works in the multimedia domain have proposed encryption approaches in the frequency domain with selective chaotic-based techniques. The idea of selective encryption was first presented by [PERSON] and [PERSON] [8] in 1995. Many research works have proposed to conduct selective encryption in the spatial domain as in [9; 10; 11; 12; 13; 14; 15; 16; 17]. Nonetheless, the frequency domain predominates the selection encryption as proposed in [18; 19; 20; 21; 22]. Though, spatial domain selective encryption is an attractive choice as it is simple and does not require any transformation of pixel intensities into other domains. The primary goal of using selective encryption algorithms is to minimize the encryption and decryption time. However, only a few research works have tried to optimize the encryption effort (time) while encrypting the data. In study [13], a novel selective symmetric encryption approach was reported for medical images. It employs GA to optimize the encryption process, in which the image is segmented into a number of regions, and the ROI is selected on the basis of pixel intensity and entropy measurements. After that, encryption algorithms with variable key lengths are selected to encrypt regions in the ROI, where each region is encrypted using an encryption algorithm that guarantees its confidentiality while minimizing the processing time. However, the bitstream of this method is not coherent; also, GA does not guarantee to find the global minimum of the optimization problem, and it does not provide a comprehensive solution. Other research works have proposed the use of swarm optimization to identify the key length that improves security or reduces the encryption time [23]. The main drawback of these optimization-based approaches is that it increases the complexity of the encryption problem. Moreover, all the referenced approaches above did not consider an objective function based on the nature of the encryption approach. Spatial domain selective encryption approaches in the literature require user input to perform segmentation (manual segmentation) and do not exploit any statistical properties of medical images. On the other hand, the frequency-based selective encryption approaches gain more attention than spatial-based ones, and most of the presented works in the frequency domain perform data selection automatically without a need for user input.