Kumar Vinod, Pathak Vinay, Badal Neelendra, Pandey Purnendu Shekhar, Mishra Rajesh, Gupta Sachin Kumar
Computers Science & Engineering Department, O P Jindal University, Raigarh, Chhattisgarh 496109 India.
Computer Science & Engineering Department, Dr. A.P.J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh 226031 India.
Multimed Tools Appl. 2022;81(26):37441-37459. doi: 10.1007/s11042-022-13546-z. Epub 2022 Jul 26.
During medical picture transmission, the most pressing concern is security. Medical images must be encrypted since they are extremely sensitive. Watermarking, digital fingerprinting/signature, and encoding are some of the available image security techniques. Images and movies, for example, must be highly encrypted and decoded without losing any content information. Medical photos, for example, require extra protection, and protecting medical images is a critical issue when medical images and related patient information are transferred over public networks. This research work proposes a visual encryption strategy to secure medical pictures before being transmitted or stored in the cloud. This technique makes such pictures of unauthorized people unavailable and also maintains confidentiality, a prime safety requirement. The process made use of a pixel shuffling-based encryption technique and a secret key created from the image. In this research, we encrypted the medical image using modified Arnold Map Encryption and generated secret key values. Therefore, the image is encrypted, and henceforth it is decrypted as well. So this work gave us the encrypted image and decrypted image/original image as well. The modified Arnold Map Encryption tries to add more randomness, thus increasing the entropy of the image and thus makes it harder to decrypt. The modified Arnold Map Encryption is also compared to other algorithms such as Hyper Chaotic, Secure Hash Algorithm-13 (SHA-13), Ten Logistic Maps, Bakers Map, HenonMap, Cross Chaos Map, and 2D Logistic Map and shows better results in terms of encryption speed and Number of Pixel Change Rate (NPCR) value.
在医学图像传输过程中,最紧迫的问题是安全性。医学图像必须加密,因为它们极其敏感。水印、数字指纹/签名和编码是一些可用的图像安全技术。例如,图像和电影必须进行高度加密和解码,且不丢失任何内容信息。例如,医学照片需要额外保护,当医学图像和相关患者信息通过公共网络传输时,保护医学图像是一个关键问题。这项研究工作提出了一种视觉加密策略,以在医学图像传输到云或存储在云之前对其进行保护。该技术使未经授权的人员无法获取此类图像,同时还能保持保密性,这是一项主要的安全要求。该过程利用了基于像素置乱的加密技术和从图像创建的密钥。在本研究中,我们使用改进的阿诺德映射加密对医学图像进行加密,并生成密钥值。因此,图像被加密,随后也被解密。所以这项工作为我们提供了加密图像以及解密图像/原始图像。改进的阿诺德映射加密试图增加更多随机性,从而增加图像的熵,进而使其更难解密。改进的阿诺德映射加密还与其他算法进行了比较,如超混沌算法、安全哈希算法 - 13(SHA - 13)、十个逻辑映射、贝克尔映射、亨农映射、交叉混沌映射和二维逻辑映射,在加密速度和像素变化率(NPCR)值方面显示出更好的结果。