Bit is the most basic unit of a digital image in the spatial domain, and bit-level encryption is regarded as an important technical means for digital image privacy protection. To address the vulnerability of image privacy protection to cryptographic attacks, in this paper, a bit-level image privacy protection scheme using Zigzag and chain-diffusion is proposed. The scheme uses a combination of Zigzag interleaving scrambling with chaotic sequences and chain-diffusion method images are encrypted at each bit level, while using non-sequential encryption to achieve efficient and secure encryption. To balance security and efficiency, the encryption strategy for each bit layer is weighted. The chaos-based sequences used for encryption depend on the previous hash value, thus the effect of chain-diffusion is achieved. To further enhance the encryption effect, a non-sequential encryption technique by non-linearly rearranging the bit cipher image is employed, so that the attacker cannot crack the protection scheme by analyzing the encrypted image. The ciphertext image hidden by discrete wavelet transform (DWT) also provides efficient encryption, higher level of security and robustness to attacks. This technology provides indistinguishable secret data embedding, making it difficult for attackers to detect or extract hidden information. Experimental results show that this scheme can effectively protect the confidentiality of the image and can resist various common cryptographic attacks. The scheme proposed in this paper is a preferred digital image privacy protection technology, so it has broad application prospects in image secure transmission occasions.
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http://dx.doi.org/10.1038/s41598-024-53325-4 | DOI Listing |
Clin Imaging
December 2024
Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India.
This letter responds to the article "Encouragement vs. liability: How prompt engineering influences ChatGPT-4's radiology exam performance," offering additional perspectives on optimising ChatGPT-4 for Radiology applications. While the study highlights the significance of prompt engineering, we suggest that addressing additional key challenges such as age-related diagnostic needs, socio-economic diversity, data security, and liability concerns is essential for responsible AI integration.
View Article and Find Full Text PDFBMC Musculoskelet Disord
December 2024
Physical medicine & rehabilitation research center, School of medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Pompe disease is a glycogen storage disease primarily affecting striated muscles. Despite its main manifestation in muscles, patients with Pompe disease may exhibit non-muscle symptoms, such as hearing loss, suggesting potential involvement of sensory organs or the nervous system due to glycogen accumulation.
Aims: This study aimed to evaluate the presence of concomitant small and large fiber neuropathy in patients with Pompe disease.
Sci Rep
December 2024
School of Electronic and Nanoscale Engineering, University of Glasgow, Glasgow, G12 8QQ, UK.
In the era of the Internet of Things (IoT), the transmission of medical reports in the form of scan images for collaborative diagnosis is vital for any telemedicine network. In this context, ensuring secure transmission and communication is necessary to protect medical data to maintain privacy. To address such privacy concerns and secure medical images against cyberattacks, this research presents a robust hybrid encryption framework that integrates quantum, and classical cryptographic methods.
View Article and Find Full Text PDFJ Imaging
December 2024
Department of Mathematics, Universität Innsbruck, Technikerstraße 13, A-6020 Innsbruck, Austria.
Medical image processing has been highlighted as an area where deep-learning-based models have the greatest potential. However, in the medical field, in particular, problems of data availability and privacy are hampering research progress and, thus, rapid implementation in clinical routine. The generation of synthetic data not only ensures privacy but also allows the drawing of new patients with specific characteristics, enabling the development of data-driven models on a much larger scale.
View Article and Find Full Text PDFJ Imaging
December 2024
Department of Pedagogy, University Rovira i Virgili, 43007 Tarragona, Spain.
Emotion recognition (ER) is gaining popularity in various fields, including education. The benefits of ER in the classroom for educational purposes, such as improving students' academic performance, are gradually becoming known. Thus, real-time ER is proving to be a valuable tool for teachers as well as for students.
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