Hybrid Hyper Chaotic Map with LSB for Image Encryption and Decryption

IF 0.9 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Scalable Computing-Practice and Experience Pub Date : 2022-12-22 DOI:10.12694/scpe.v23i4.2018
Jahnavi Shankar, C. Nandini
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引用次数: 3

Abstract

There are number of images that transmitted through the web for various usages like medical imaging, satellite images, military database, broadcasting, confidential enterprise, banking, etc. Thus, it is important to protect the images confidentially by securing sensitive information from an intruder. The present research work proposes a Hybrid Hyper Chaotic Mapping that considers a3D face Mesh model for hiding the secret image. The model has a larger range of chaotic parameters which are helpful in the chaotification approaches. The proposed system provides excellent security for the secret image through the process of encryption and decryption. The encryption of the secret image is performed by using chaos encryption with hyper hybrid mapping. The hyper hybrid mapping includes enhanced logistic and henon mapping to improve the computation efficiency for security to enhance embedding capacity. In the experiment Fingerprint and satellite image is used as secret image. The secret image is encrypted using a Least Significant Bit (LSB) for embedding an image. The results obtained by the proposed method showed better enhancements in terms of SNR for the 3D Mesh model dataset as 77.85 dB better compared to the existing models that achieved Reversible data hiding in the encrypted domain (RDH-ED) of 33.89 dB and Multiple Most Significant Bit (Multi-MSB) 40 dB. Also, the results obtained by the proposed Hybrid Hyper chaotic mapping showed PSNR of 65.73 dB better when compared to the existing Permutation Substitution and Boolean Operation that obtained 21.19 dB and 21.27 dB for the Deoxyribonucleic Acid (DNA) level permutation-based logistic map.
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基于LSB的混合超混沌映射图像加解密算法
有许多图像通过网络传输,用于各种用途,如医学成像、卫星图像、军事数据库、广播、机密企业、银行等。因此,重要的是通过保护敏感信息免受入侵者的机密性来保护图像。本研究提出了一种混合超混沌映射方法,该方法考虑三维人脸网格模型来隐藏秘密图像。该模型具有更大的混沌参数范围,这有助于混沌化方法。该系统通过加密和解密的过程为秘密图像提供了良好的安全性。采用超混合映射的混沌加密方法对秘密图像进行加密。超混合映射包括增强逻辑映射和henon映射,以提高计算效率,增强嵌入容量。实验采用指纹和卫星图像作为秘密图像。使用最低有效位(LSB)对秘密图像进行加密以嵌入图像。结果表明,该方法对三维网格模型数据集的信噪比提高了77.85 dB,而现有模型的加密域(RDH-ED)的可逆数据隐藏率为33.89 dB,多重最有效位(Multi-MSB)为40 dB。此外,与现有的基于脱氧核糖核酸(DNA)水平置换的逻辑图的21.19 dB和21.27 dB的置换置换和布尔运算相比,本文提出的混合超混沌映射的PSNR为65.73 dB。
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来源期刊
Scalable Computing-Practice and Experience
Scalable Computing-Practice and Experience COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.00
自引率
0.00%
发文量
10
期刊介绍: The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.
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