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<p>As the Internet era progressively transitions from Web2.0 to Web3.0, the value of image data is steadily increasing. To ensure user interests, an image encryption algorithm based on 2D compressed sensing and 2D chaotic systems has been introduced. Firstly, we investigate the compressed sensing technique and identify a key issue: while chaos-based compressed sensing exhibits strong plaintext sensitivity. Therefore, this paper introduces a novel 2D chaotic system capable of concurrently generating two unrelated chaotic sequences—the sequences serve as measurement matrices for the rows and columns of two-dimensional compressive sensing, while also being applicable to the scrambling process in image encryption. Secondly, compared to high-dimensional chaotic matrices, two-dimensional chaotic matrices exhibit the advantages of simplicity in construction and lower computational complexity. Simultaneously, to further reduce the computational complexity of this image encryption algorithm, the present study innovatively employs binary measurement matrices during the two-dimensional compressive sensing process. Thirdly, conventional compressed sensing calculations typically involve transforming two-dimensional images into one-dimensional vectors before applying the measurement matrix. This process consumes substantial storage space and increases algorithmic complexity. Unlike traditional compressed sensing methods that require converting 2D images into 1D vectors before applying the measurement matrix—resulting in high storage demands and increased computational complexity—our approach directly applies 2D compressed sensing along the image’s rows and columns. This allows compression calculations to be directly conducted along rows and columns, enhancing the efficiency of the algorithm’s execution. This innovative approach aligns with the evolving landscape of Web3.0, providing a secure and efficient solution for safeguarding the escalating value of image data. The results of the experiments indicate that the proposed encryption algorithm can effectively resist statistical attacks, brute-force attacks, and plaintext attacks on images. Additionally, the method demonstrates good compression effects and robustness.</p>

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Advanced image encryption algorithm for Web3.0

  • 期刊论文

  • 发表日期：

    2025年9月3日

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  • Zhi Zhou,
  • Guanyan He,
  • Yuqiang Dou

摘要

As the Internet era progressively transitions from Web2.0 to Web3.0, the value of image data is steadily increasing. To ensure user interests, an image encryption algorithm based on 2D compressed sensing and 2D chaotic systems has been introduced. Firstly, we investigate the compressed sensing technique and identify a key issue: while chaos-based compressed sensing exhibits strong plaintext sensitivity. Therefore, this paper introduces a novel 2D chaotic system capable of concurrently generating two unrelated chaotic sequences—the sequences serve as measurement matrices for the rows and columns of two-dimensional compressive sensing, while also being applicable to the scrambling process in image encryption. Secondly, compared to high-dimensional chaotic matrices, two-dimensional chaotic matrices exhibit the advantages of simplicity in construction and lower computational complexity. Simultaneously, to further reduce the computational complexity of this image encryption algorithm, the present study innovatively employs binary measurement matrices during the two-dimensional compressive sensing process. Thirdly, conventional compressed sensing calculations typically involve transforming two-dimensional images into one-dimensional vectors before applying the measurement matrix. This process consumes substantial storage space and increases algorithmic complexity. Unlike traditional compressed sensing methods that require converting 2D images into 1D vectors before applying the measurement matrix—resulting in high storage demands and increased computational complexity—our approach directly applies 2D compressed sensing along the image’s rows and columns. This allows compression calculations to be directly conducted along rows and columns, enhancing the efficiency of the algorithm’s execution. This innovative approach aligns with the evolving landscape of Web3.0, providing a secure and efficient solution for safeguarding the escalating value of image data. The results of the experiments indicate that the proposed encryption algorithm can effectively resist statistical attacks, brute-force attacks, and plaintext attacks on images. Additionally, the method demonstrates good compression effects and robustness.