Yildirim Melih
The Scientific and Technological Research Council of Turkey (TUBITAK), Ankara, Turkey.
Nonlinear Dyn. 2021;105(3):2677-2692. doi: 10.1007/s11071-021-06700-z. Epub 2021 Jul 22.
A novel image steganography technique in order to hide the ciphered voice data has been suggested in this work. The doctor's voice comments belonging to a coronavirus disease 2019 (COVID-19) patient are hidden in a medical image in order to protect the patient information. The introduced steganography technique is based on chaos theory. Firstly, the voice comments of the doctor are converted to an image and secondly, they are ciphered utilizing the suggested encryption algorithm based on a chaotic system. Then, they are embedded into the cover medical image. A lung angiography dual-energy computed tomography (CT) scan of a COVID-19 patient is used as a cover object. Numerical and security analyses of steganography method have been performed in MATLAB environment. The similarity metrics are calculated for R, G, B components of cover image and stego image as visual quality analysis metrics to examine the performance of the introduced steganography procedure. For a 512 × 512 pixel cover image, SSIM values are obtained as 0.8337, 0.7926, and 0.9273 for R, G, B components, respectively. Moreover, security analyses which are differential attack, histogram, information entropy, correlation of neighboring pixels and the initial condition sensitivity are carried out. The information entropy is calculated as 7.9993 bits utilizing the suggested steganography scheme. The mean value of the ten UACI and NPCR values are obtained as 33.5688% and 99.8069%, respectively. The results of security analysis have revealed that the presented steganography procedure is able to resist statistical attacks and the chaotic system-based steganography scheme shows the characteristics of the sensitive dependence on the initial condition and the secret key. The proposed steganography method which is based on a chaotic system has superior performance in terms of being robust against differential attack and hiding encrypted voice comments of the doctor. Moreover, the introduced algorithm is also resistant against exhaustive, known plaintext, and chosen plaintext attacks.
本研究提出了一种用于隐藏加密语音数据的新型图像隐写技术。为保护患者信息，将属于一名2019冠状病毒病（COVID-19）患者的医生语音评论隐藏在医学图像中。所引入的隐写技术基于混沌理论。首先，将医生的语音评论转换为图像，其次，利用基于混沌系统的建议加密算法对其进行加密。然后，将它们嵌入到封面医学图像中。一名COVID-19患者的肺部血管造影双能计算机断层扫描（CT）图像用作封面对象。在MATLAB环境中对隐写方法进行了数值和安全性分析。计算封面图像和隐写图像的R、G、B分量的相似性度量，作为视觉质量分析指标，以检验所引入的隐写过程的性能。对于一幅512×512像素的封面图像，R、G、B分量的结构相似性（SSIM）值分别为0.8337、0.7926和0.9273。此外，还进行了差分攻击、直方图、信息熵、相邻像素相关性和初始条件敏感性等安全性分析。利用所建议的隐写方案计算出信息熵为7.9993比特。十个通用平均变化强度（UACI）和归一化像素改变率（NPCR）值的平均值分别为33.5688%和99.8069%。安全性分析结果表明，所提出的隐写过程能够抵抗统计攻击，基于混沌系统的隐写方案表现出对初始条件和密钥敏感依赖的特性。所提出的基于混沌系统的隐写方法在抵抗差分攻击和隐藏医生加密语音评论方面具有优越的性能。此外，所引入的算法还能抵抗穷举攻击、已知明文攻击和选择明文攻击。
