A high-capacity adaptive steganographic encryption algorithm for NFT images based on HPM hyperchaotic map-driven bidirectional spiral scrambling and dynamic Morse code diffusion

IF 2.9 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Yuxi Wang, Lin Teng
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Abstract

Non-fungible token (NFT) images, with their uniqueness enabled by blockchain, are transforming from technological experiments into core assets that drive digital art and the metaverse economy. However, an important pain point of NFT images is the risk of leakage during transmission. This paper introduces an adaptive capacity low-bit steganography method for NFT image encryption based on bidirectional spiral scrambling and dynamic Morse code diffusion driven by hyperbolic phase-modulated chaotic map (HPM) hyperchaotic system. The HPM hyperchaotic system with double positive Lyapunov exponents has stronger cryptographic resistance and dynamic unpredictability than the traditional two-dimensional systems with only a single positive Lyapunov exponents. The bidirectional spiral scrambling method only takes O(N) time complexity to achieve complete visual scrambling of the secret image, where N is the total number of pixels to be permuted. The chaotic sequence, processed by a multi-level dynamic encoding module and linear confusion, is subsequently XORed with the permuted NFT image to achieve pixel value diffusion. This step completely dissolves the connection between pixels and completes the encryption of the NFT image. The chaotic sequence is used as an index to embed the adaptive capacity of the encrypted image into the low bits of the pixel value of the cover image. Chaotic encrypted of NFT images and embedded them into cover images using low-bit steganography technology can achieve covert transmission, evade network sniffing, and reduce the risk of leakage. Relevant experimental results show that at a high embedding capacity of 6.0 bpp, the Peak Signal-to-Noise Ratio (PSNR) is greater than 44.0 and the Structural Similarity Index (SSIM) is greater than 0.97, which meets the security requirements of financial data encryption. It not only ensures the quality of the stego image, but also enhances the robustness of the embedded information. At the same time, the encrypted steganography algorithm has significant resistance to common attacks such as cropping and salt and pepper noise, ensuring that the embedded information can still be effectively extracted in an interference environment.

Abstract Image

Abstract Image

基于HPM超混沌映射驱动双向螺旋置乱和动态摩尔斯电码扩散的NFT图像大容量自适应隐写加密算法
不可替代代币(NFT)图像,凭借区块链的独特性,正在从技术实验转变为推动数字艺术和虚拟经济的核心资产。然而,NFT图像的一个重要痛点是传输过程中的泄漏风险。介绍了一种基于双曲调相混沌映射(HPM)超混沌系统驱动的双向螺旋置乱和动态摩尔斯电码扩散的自适应容量低比特隐写NFT图像加密方法。具有双正Lyapunov指数的HPM超混沌系统比具有单正Lyapunov指数的传统二维系统具有更强的抗密码性和动态不可预测性。双向螺旋置乱方法只需要O(N)的时间复杂度就可以实现对秘密图像的完全视觉置乱,其中N为需要排列的像素总数。混沌序列经过多级动态编码模块和线性混淆处理后,与置换后的NFT图像xor,实现像素值扩散。这一步完全解除了像素之间的连接,完成了对NFT图像的加密。利用混沌序列作为索引,将加密图像的自适应能力嵌入到封面图像像素值的低位。利用低比特隐写技术对NFT图像进行混沌加密并嵌入到掩蔽图像中,可以实现隐蔽传输,规避网络嗅探,降低泄漏风险。相关实验结果表明,在6.0 bpp的高嵌入容量下,峰值信噪比(PSNR)大于44.0,结构相似指数(SSIM)大于0.97,满足金融数据加密的安全要求。它既保证了隐写图像的质量,又增强了嵌入信息的鲁棒性。同时,加密隐写算法对常见的剪切、椒盐噪声等攻击具有显著的抵抗能力,确保在干扰环境下仍能有效提取嵌入信息。
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来源期刊
The European Physical Journal Plus
The European Physical Journal Plus PHYSICS, MULTIDISCIPLINARY-
CiteScore
5.40
自引率
8.80%
发文量
1150
审稿时长
4-8 weeks
期刊介绍: The aims of this peer-reviewed online journal are to distribute and archive all relevant material required to document, assess, validate and reconstruct in detail the body of knowledge in the physical and related sciences. The scope of EPJ Plus encompasses a broad landscape of fields and disciplines in the physical and related sciences - such as covered by the topical EPJ journals and with the explicit addition of geophysics, astrophysics, general relativity and cosmology, mathematical and quantum physics, classical and fluid mechanics, accelerator and medical physics, as well as physics techniques applied to any other topics, including energy, environment and cultural heritage.
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