Article
Green & Sustainable Science & Technology
Marwa Obayya, Majdy M. Eltahir, Olayan Alharbi, Mashael Maashi, Abeer S. Al-Humaimeedy, Najm Alotaibi, Mohammed K. Nour, Manar Ahmed Hamza
Summary: With the development of artificial technologies, smart healthcare systems have become increasingly important in healthcare. This paper proposes a compression then encryption model for secure healthcare data storage and access management in cloud server. The model utilizes data compression and encryption techniques to effectively utilize resources and ensure data security.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Computer Science, Information Systems
A. Christoper Tamilmathi, P. L. Chithra
Summary: This paper introduces a novel and efficient codec for 3D LiDAR point cloud images, using block-wise decomposition and quantization methods to compress tensor structured signal data. Experimental results show that the proposed algorithm outperforms other common compression techniques in terms of compression efficiency and image quality.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Omar El Ogri, Hicham Karmouni, Mhamed Sayyouri, Hassan Qjidaa
Summary: One major application of the fractional-order discrete transform (FrDTs) is in signal and information security, especially in signal and image/video encryption. Researchers have recently proposed techniques that implement not only the fractional transforms but also randomized versions of the FrDTs, adding more security features to signal encryption. This paper introduces a new image/video encryption scheme based on fractional-order discrete Tchebichef transform (FrDTT) using singular value decomposition, showing promising results in terms of effectiveness and efficiency.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Adnan Malik, Muhammad Ali, Faisal S. Alsubaei, Nisar Ahmed, Harish Kumar
Summary: This study introduces a color image encryption method that combines four chaotic systems, utilizing singular value decomposition and a chaotic sequence, making it secure and compression-friendly. The proposed approach is shown to be secure against a wide range of attacks and provides superior compression friendliness when compared to chaos-based alternatives through thorough investigation of experimental data.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Satendra Pal Singh, Gaurav Bhatnagar
Summary: In this article, a novel biometric-inspired medical encryption technique using PR-APBST, singular value, and QR decomposition is proposed. The technique utilizes biometrics of the patient/owner to generate a key management system for parameter retrieval, encrypting medical images for secure transmission or storage, and employing a reliable decryption process for reconstruction. Extensive experiments on various medical images and security analyses have demonstrated the validity and feasibility of the proposed framework.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2021)
Article
Mathematics, Interdisciplinary Applications
Guodong Ye, Huishan Wu, Min Liu, Xiaoling Huang
Summary: In this paper, a reversible image-hiding algorithm based on a novel chaotic system is proposed using compressive sensing and singular value sampling techniques. The algorithm extracts the plain messages from the secret image and encrypts them using the RSA algorithm. It then transforms the messages into initial keys, which are used to produce a random key stream. The secret image is scrambled and partitioned, and the non-zero blocks are sampled using CS. The new sampling values are embedded into the wavelet coefficients to obtain a new carrier image containing the secrets.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Computer Science, Artificial Intelligence
Yaomin Wang, Gangqiang Xiong, Wenguang He
Summary: This paper proposes a new method of reversible data hiding in encrypted images for protecting the privacy of image owners in Industrial Internet of Things (IIoT). The method achieves high capacity data hiding by using block-level image encryption and pixel-value ordering techniques while maintaining image reversibility. Experimental results demonstrate that the method significantly improves embedding capacity without destroying reversibility.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Yongfei Wu, Liming Zhang, Tao Qian, Xilin Liu, Qiwei Xie
Summary: This study presents a novel image encryption cryptosystem based on two-dimensional partial unwinding decomposition (2D-PUD) and diffusion scheme for generating security key and cipher image. The adaptive attribute of the 2D-PUD results in completely distinct 1D decomposition components for different images, effectively resisting cryptographic attacks.
Article
Multidisciplinary Sciences
Qinghua Song, Arthur Baroni, Pin Chieh Wu, Sebastien Chenot, Virginie Brandli, Stephane Vezian, Benjamin Damilano, Philippe de Mierry, Samira Khadir, Patrick Ferrand, Patrice Genevet
Summary: A novel method utilizing vectorial Fourier metasurfaces to decouple and encrypt intensity and polarization information was proposed, enabling customizable optical field distribution and expanding research in optical encryption.
NATURE COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Ahmed Elmoasry, Lal Said Khan, Majid Khan, Iqtadart Hussain
Summary: This paper proposes a dual-layer security scheme based on the Internet of Medical Things (IoMT) to protect the data security and privacy of medical images. The proposed scheme utilizes diffusion and confusion encryption algorithms and Hessenberg and singular value decomposition (SVD) for data hiding to provide dual security protection. Experimental results demonstrate the strong security of the proposed scheme in both encryption and data hiding.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Mathematics
Mengyao Li, Xianwen Fang, Asimeng Ernest
Summary: To protect the privacy and security of stakeholders, it is necessary to encrypt flowcharts, and a proposed encryption method is based on dynamic selection chaotic system and singular value decomposition. The method includes constructing a dynamic selected chaotic system, merging the process image into a gray matrix using neural network, scrambling the matrix based on singular value decomposition, proposing a new subdivision diffusion method using the dynamic selected chaotic system, and encrypting the color image into single grayscale ciphertext using asymmetric encryption. Simulation results and performance analysis show that the proposed method has good encryption performance.
Article
Automation & Control Systems
Weikang Wang, Chang Chen, Wenxuan Yao, Kaiqi Sun, Wei Qiu, Yilu Liu
Summary: This article proposes a novel model combining cross entropy and singular value decomposition, which can compress synchrophasor data to an extremely small size while maintaining superior accuracy and retaining critical information under disturbance conditions.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Information Systems
Sandeep Kumar Raghuwanshi, Rajesh Kumar Pateriya
Summary: Neighborhood-based Collaborative Filtering techniques have limitations in dealing with scalable and sparse data, hindering the efficiency of recommendation systems. This study introduces a new filtering technique that accelerates Singular Value Decomposition using Stochastic Gradient Descent optimization, resulting in faster convergence of learning parameters and improved classification accuracy.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2021)
Article
Engineering, Multidisciplinary
Mohamed Meselhy Eltoukhy, Ayman E. Khedr, Mostafa M. Abdel-Aziz, Khalid M. Hosny
Summary: This paper proposes a new robust watermarking method that combines Slant, Singular Value Decomposition (SVD), and quaternion Fourier-Transform (QFT) for securing color medical images. The method involves splitting the input image into four parts, encrypting them using OTP encryption, applying Slant transform for compaction, applying SVD for quality preservation, and applying QFT for imperceptibility. The proposed method achieves a good tradeoff between invisibility and robustness compared to existing schemes, and attains high visual imperceptibility.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Chemistry, Analytical
Genki Hamano, Shoko Imaizumi, Hitoshi Kiya
Summary: This paper evaluates the effects of JPEG compression on image classification using the Vision Transformer (ViT). The study demonstrates that JPEG compression can significantly reduce the amount of encrypted image data while maintaining classification accuracy, making it the first study to classify JPEG-compressed encrypted images without sacrificing high accuracy.
