A High-Performance Fractal Encryption Framework and Modern Innovations for Secure Image Transmission

• URL: http://arxiv.org/abs/2601.20374v1
• Date: Wed, 28 Jan 2026 08:37:10 GMT
• Title: A High-Performance Fractal Encryption Framework and Modern Innovations for Secure Image Transmission
• Authors: Sura Khalid Salsal, Eman Shaker Mahmood, Farah Tawfiq Abdul Hussien, Maryam Mahdi Alhusseini, Azhar Naji Alyahya, Nikolai Safiullin,
• Abstract summary: Classical encryption algorithms suffer from a trade-off among security, image fidelity, and computational efficiency.<n>This is done by proposing Fractal encryption based on Fourier transforms as a new method of image encryption.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The current digital era, driven by growing threats to data security, requires a robust image encryption technique. Classical encryption algorithms suffer from a trade-off among security, image fidelity, and computational efficiency. This paper aims to enhance the performance and efficiency of image encryption. This is done by proposing Fractal encryption based on Fourier transforms as a new method of image encryption, leveraging state-of-the-art technology. The new approach considered here intends to enhance both security and efficiency in image encryption by comparing Fractal Encryption with basic methods. The suggested system also aims to optimise encryption/ decryption times and preserve image quality. This paper provides an introduction to Image Encryption using the fractal-based method, its mathematical formulation, and its comparative efficiency against publicly known traditional encryption methods. As a result, after filling the gaps identified in previous research, it has significantly improved both its encryption/decryption time and image fidelity compared to other techniques. In this paper, directions for future research and possible improvements are outlined for attention.

Related papers

• Image Encryption Using DNA Encoding, Snake Permutation and Chaotic Substitution Techniques [0.7743851353380347]
  This paper presents a new image encryption scheme using DNA encoding, snake permutation and chaotic substitution techniques.<n>DNA encoding and snake permutation modules ensure effective scrambling of the pixels.<n>For the confusion part, the chaotic substitution technique is implemented, which substitutes the pixel values chosen randomly from 3 S-boxes.
  arXiv  Detail & Related papers  (2025-03-12T03:54:37Z)
• Secure Semantic Communication With Homomorphic Encryption [52.5344514499035]
  This paper explores the feasibility of applying homomorphic encryption to SemCom.<n>We propose a task-oriented SemCom scheme secured through homomorphic encryption.
  arXiv  Detail & Related papers  (2025-01-17T13:26:14Z)
• Enabling Practical and Privacy-Preserving Image Processing [5.526464269029825]
  Homomorphic Encryption (FHE) enables computations on encrypted data, preserving confidentiality without the need for decryption. Traditional FHE methods often encrypt images by monolithic data blocks, instead of pixels. We propose and implement a pixel-level homomorphic encryption approach, iCHEETAH, based on the CKKS scheme.
  arXiv  Detail & Related papers  (2024-09-05T14:22:02Z)
• Deep Learning and Chaos: A combined Approach To Image Encryption and Decryption [1.8749305679160366]
  We introduce a novel image encryption and decryption algorithm using hyperchaotic signals from the novel 3D hyperchaotic map, 2D memristor map, Convolutional Neural Network (CNN) The robustness of the encryption algorithm is shown by key sensitivity analysis, i.e., the average sensitivity of the algorithm to key elements.
  arXiv  Detail & Related papers  (2024-06-24T16:56:22Z)
• A Hybrid Image Encryption Scheme based on Chaos and a DPA-Resistant Sbox [0.0]
  Recently, Khalid M. Hosny presented an image encryption scheme based on 6D hyper chaotic mapping and Q-Fibonacci matrix. In this paper, based on Khaled Hosny's design, a new effective design is presented that has improved encryption security and efficiency.
  arXiv  Detail & Related papers  (2023-12-23T15:26:15Z)
• Perceptual Image Compression with Cooperative Cross-Modal Side Information [53.356714177243745]
  We propose a novel deep image compression method with text-guided side information to achieve a better rate-perception-distortion tradeoff. Specifically, we employ the CLIP text encoder and an effective Semantic-Spatial Aware block to fuse the text and image features.
  arXiv  Detail & Related papers  (2023-11-23T08:31:11Z)
• PRO-Face S: Privacy-preserving Reversible Obfuscation of Face Images via Secure Flow [69.78820726573935]
  We name it PRO-Face S, short for Privacy-preserving Reversible Obfuscation of Face images via Secure flow-based model. In the framework, an Invertible Neural Network (INN) is utilized to process the input image along with its pre-obfuscated form, and generate the privacy protected image that visually approximates to the pre-obfuscated one.
  arXiv  Detail & Related papers  (2023-07-18T10:55:54Z)
• Human-imperceptible, Machine-recognizable Images [76.01951148048603]
  A major conflict is exposed relating to software engineers between better developing AI systems and distancing from the sensitive training data. This paper proposes an efficient privacy-preserving learning paradigm, where images are encrypted to become human-imperceptible, machine-recognizable'' We show that the proposed paradigm can ensure the encrypted images have become human-imperceptible while preserving machine-recognizable information.
  arXiv  Detail & Related papers  (2023-06-06T13:41:37Z)
• RiDDLE: Reversible and Diversified De-identification with Latent Encryptor [57.66174700276893]
  This work presents RiDDLE, short for Reversible and Diversified De-identification with Latent Encryptor. Built upon a pre-learned StyleGAN2 generator, RiDDLE manages to encrypt and decrypt the facial identity within the latent space.
  arXiv  Detail & Related papers  (2023-03-09T11:03:52Z)
• SISA: Securing Images by Selective Alteration [0.0]
  We present a comparative analysis of the partial and full encryption of the photos. Instead of encrypting or blurring the entire photograph, we only encode selected regions of the image. We leverage the machine learning algorithms like Mask-RCNN and YOLO to select the region of interest.
  arXiv  Detail & Related papers  (2021-06-20T05:31:47Z)
• HERS: Homomorphically Encrypted Representation Search [56.87295029135185]
  We present a method to search for a probe (or query) image representation against a large gallery in the encrypted domain. Our encryption scheme is agnostic to how the fixed-length representation is obtained and can therefore be applied to any fixed-length representation in any application domain.
  arXiv  Detail & Related papers  (2020-03-27T01:10:54Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.