Protecting digital data, especially digital images, from unauthorized access and malicious activities is crucial in today's digital era. This paper introduces a novel approach to enhance image encryption by combining the strengths of the RSA algorithm, homomorphic encryption, and chaotic maps, specifically the sine and logistic map, alongside the self-similar properties of the fractal Sierpinski triangle. The proposed fractal-based hybrid cryptosystem leverages Paillier encryption for maintaining security and privacy, while the chaotic maps introduce randomness, periodicity, and robustness. Simultaneously, the fractal Sierpinski triangle generates intricate shapes at different scales, resulting in a substantially expanded key space and heightened sensitivity through randomly selected initial points. The secret keys derived from the chaotic maps and Sierpinski triangle are employed for image encryption. The proposed scheme offers simplicity, efficiency, and robust security, effectively safeguarding against statistical, differential, and brute-force attacks. Through comprehensive experimental evaluations, we demonstrate the superior performance of the proposed scheme compared to existing methods in terms of both security and efficiency. This paper makes a significant contribution to the field of digital image encryption, paving the way for further exploration and optimization in the future.
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http://dx.doi.org/10.3390/e25111478 | DOI Listing |
Spectrochim Acta A Mol Biomol Spectrosc
December 2024
School of Chemistry and Chemical Engineering, Shaanxi Key Laboratory of Chemical Reaction Engineering, Laboratory of New Energy & New Function Materials, Yanan University, Yan'an 716000, China.
Elemental analysis, infrared spectroscopy, and X-ray single crystal diffraction indicated that a novel metal-organic framework (Tb-MOF) designated as 0.5n[Hbpy]·[Tb(dpa)(HO)]·4nHO was synthesized successfully, (where Hdpa = 5-(3, 4-dicarboxy- phenoxy) isophenic acid, bpy = protonated 4,4'-bipyridine). Tb-MOF adopts a 3D network structure based on Tb ions and the (dpa) ligand through µ: η, η, η, η binding modes.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
College of Computer, Chongqing University, No. 55 Daxuecheng South Rd, Shapingba, 401331, Chongqing, China.
Convolutional neural networks (CNNs) have become indispensable to medical image diagnosis research, enabling the automated differentiation of diseased images from extensive medical image datasets. Due to their efficacy, these methods raise significant privacy concerns regarding patient images and diagnostic models. To address these issues, some researchers have explored privacy-preserving medical image diagnosis schemes using fully homomorphic encryption (FHE).
View Article and Find Full Text PDFSci Rep
January 2025
Universidad Europea del Atlántico. Isabel Torres 21, Santander, 39011, Spain.
Steganography is used to hide sensitive types of data including images, audio, text, and videos in an invisible way so that no one can detect it. Image-based steganography is a technique that uses images as a cover media for hiding and transmitting sensitive information over the internet. However, image-based steganography is a challenging task due to transparency, security, computational efficiency, tamper protection, payload, etc.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Science and Technology, Charles Darwin University, Casuarina, NT, 0909, Australia.
This study presents a novel privacy-preserving self-supervised (SSL) framework for COVID-19 classification from lung CT scans, utilizing federated learning (FL) enhanced with Paillier homomorphic encryption (PHE) to prevent third-party attacks during training. The FL-SSL based framework employs two publicly available lung CT scan datasets which are considered as labeled and an unlabeled dataset. The unlabeled dataset is split into three subsets which are assumed to be collected from three hospitals.
View Article and Find Full Text PDFACS Nano
January 2025
Center for High Pressure Science (CHiPS), State Key Laboratory of Metastable Materials Science & Technology, Yanshan University, Qinhuangdao 066004, China.
Moiré superlattices, created by stacking different van der Waals materials at twist angles, have emerged as a versatile platform for exploring intriguing phenomena such as topological properties, superconductivity, the quantum anomalous Hall effect, and the unconventional Stark effect. Additionally, the formation of moiré superlattice potential can generate spontaneous symmetry breaking, leading to an anisotropic optical response and electronic transport behavior. Herein, we propose a two-step chemical vapor deposition (CVD) strategy for synthesizing WS/SbS moiré superlattices.
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