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检索条件"任意字段=4th Conference on Mathematics of Image and Data Coding, Compression, and Encryption"

共 248 条记录，以下是1-10 订阅

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Cryptographic image Security Using AES-XOR Approach 4

Cryptographic Image Security Using AES-XOR Approach

引用

4th International conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Santhosh, B. Kushmitha, V. Bhat, Samhita Mondal, Satyaki Joshitha, V. Dayananda Sagar College of Engineering Dept. of Electronics and Telecommunication Bangalore India

ISBN: (纸本)9798331523923

the primary objective of this project is to enhance the security of digital images transmitted over open networks by addressing privacy risks through cryptographic techniques. Recent image encryption methods, such as chaotic-based algorithms, permutation techniques, and DNA coding, have shown promise but face significant challenges. these include limited key sensitivity, computational inefficiency, pattern retention in encrypted images, and susceptibility to cryptanalytic attacks like brute force and differential analysis. To address these issues, this project proposes a dual-layer encryption approach combining the Advanced encryption Standard (AES) algorithm and a randomized AES-compatible key generator. In the first step, the AES algorithm is applied to the plain image, creating a strong initial encryption layer. Next, an AES-compatible key generator produces a randomized key, which is used in an XOR operation to add an additional layer of security. this two-step process ensures that encrypted images exhibit highly randomized outputs, with histograms that differ significantly from the original images, thus eliminating statistical patterns and mitigating statistical attacks. the proposed encryption method successfully enhances security by producing highly randomized encryption results, with the histogram of the encrypted image differing significantly from that of the original image. this dual-layered approach to encryption demonstrates robustness against conventional decryption attempts and strengthens the data integrity of the encrypted images. © 2025 IEEE.

关键词： AES image Processing Security and Privacy XOR Operation

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Secure Medical Imaging: A DICOM to JPEG 2000 Conversion Algorithm with Integrated encryption 4

Secure Medical Imaging: A DICOM to JPEG 2000 Conversion Algo...

引用

4th IEEE International conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Siam, Abdullah Al Hassan, Md Maruf Bhuiyan, Touhid Daffodil International University Department of Software Engineering Dhaka Bangladesh Southeast University Department of CSE Bangladesh Washington University of Science and Technology School of IT VA United States

ISBN: (纸本)9798331518882

this study aims to develop a secure and effective framework for converting DICOM (Digital Imaging and Communications in Medicine) to JPEG 2000 to protect the integrity of medical images. the proposed approach uses Python tools to convert DICOM data to the JPEG 2000 format, using AES encryption and SHA-256 for key generation in CBC mode. Our results indicate that the proposed framework enhances data confidentiality by reducing unauthorized access risk, image quality, compression efficiency, and decryption reliability. the findings with the conversion to JPEG 2000 format for storage efficiency were raised by 79.9% while keeping the quality of the diagnostic photographs. Private medical data was insulated from illegal access by AES encryption. Decryption tests confirmed that the original image could be restored without losing diagnostic information, and using CBC mode increased security by encrypting each image independently. this combined approach encourages improved management of medical images by tackling the problems of size and security in healthcare settings and adds robustness to digital confidentiality. the framework is applicable to connect with PACS to improve data management and be used to safely archive medical pictures. © 2025 IEEE.

关键词： Digital Imaging and Communications in Medicine (DICOM)

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Lightweight security Mechanism for IoT Applications using Substitution-Box 4

Lightweight security Mechanism for IoT Applications using Su...

引用

4th IEEE International conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Hanif, Fozia Shams, Rehan Waheed, Urooj University of Karachi Department of Mathematics Karachi Pakistan Sir Syed University of Engineering and Technology Karachi Department of Telecommunication Pakistan DHA Suffa University Karachi Department of Computer Science Pakistan

ISBN: (纸本)9798331518882

In recent times the use of small computing devices for gathering information from the real world is increasing day by day. the devices like wireless sensors, RIFD tags, embedded devices and IoT devices are required to transmit huge amounts of confidential data for monitoring and controlling. IoT applications have now become an important factor across various industries. that is why the security of IoT device is always been an important issue, because they transmit private and sensitive data. For handling the security issue cryptography is one the way for handling the security issues of IoT devices but sometimes cryptographic algorithms are cracked and as well as very costly. Lightweight cryptography requires less memory and less computational cost. Substitution box is a very useful concept in generating the lightweight cryptographic algorithm that provide robust security in the process of encryption. this study produces lightweight cryptographic encryption and decryption algorithm with the help of substitution boxes. the provided scheme not only provides the encryption procedure but also generating a flexible key structure which enhances the security for IoT devices where lightweight image encryption is crucial. the provided technique will be beneficial for those places where confidential public data has to be secured. the aim of this paper is to recommend effective original and straightforward techniques of encryption and decryption by using the substitution box. Experimental results show the efficiency of the suggested technique in terms of execution time and throughput. © 2025 IEEE.

关键词： encryption algorithms

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Enhancing the Compressed Video Quality through a Neural Network Approach 4

Enhancing the Compressed Video Quality through a Neural Netw...

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4th International conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Panneerselvam, Karthick Rajalakshmi, K. Sornalatha, P. Kpr Institute of Engineering and Technology Department of Computer Science & Engineering Tamil Nadu Uthupalayam641407 India Cmr Institute of Technology Department of Mca Karnataka Bengaluru560037 India Alagappa University Department of Computer Applications Tamil Nadu Karaikudi630003 India

ISBN: (纸本)9798331523923

Video compression mainly focuses on reducing the file size of videos with little loss of quality, but most video compression algorithms on the market do not focus on clarity. data compression is increasingly being considered as a necessary issue in larger engineering communities. data compression using neural networks has been the main topic of some related research. the main objective of this study would be to apply the video in an amazing way with the help of an Enhanced Generative Adversarial Network (EGAN). EGAN was better to manage and produced better consistent results with fewer artifacts than other Neural Networks (NN). Deep neural networks (DNNs), recurrent neural networks (RNNs), generational adversarial networks (GANs), and various autoencoder (AE) variants have all been used for various compression methods. It would be a potential option for incredible movies. Based on significantly reduced sample input films, the proposed neural network was able to maintain high-frequency information and generate pleasurable sensory videos. A Residual Dense Block (RDB) is the sort of block utilized in the design. In comparison to previous state-of-the-art approaches, the comprehensive Mean-Opinion-Score (MOS) test, and the Video Multi-Method Assessment Fusion (VMMAF) test, reveal extremely substantial increases in terms of human experiential accuracy. the researchers are also proposing a new data pre-processing method based on the Deep Recurrent Neural Network (DRNN) that has been combined with two leading-edge coding standards, and the Adaptable Video coding (AVC). the results show consistent encoding benefits across all sequences examined at multiple spatial frequencies, with an average bit rate savings of 4.0 percent relative to AVC. © 2025 IEEE.

关键词： image coding

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Secure Medical Imaging: A DICOM to JPEG 2000 Conversion Algorithm with Integrated encryption

Secure Medical Imaging: A DICOM to JPEG 2000 Conversion Algo...

引用

AI in Cybersecurity (ICAIC), International conference on

作者： Abdullah Al Siam Md Maruf Hassan Touhid Bhuiyan Department of Software Engineering Daffodil International University Dhaka Bangladesh Department of CSE Southeast University Bangladesh School of IT Washington University of Science and Technology VA USA

ISBN: (数字)9798331518882

ISBN: (纸本)9798331518899

关键词： image quality image coding Transform coding Picture archiving and communication systems Robustness encryption DICOM Medical diagnostic imaging Secure storage Testing

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image encryption ALGORIthM BASED ON WIDELY CHAOTIC 5D SYSTEMS AND DNA coding 25

IMAGE ENCRYPTION ALGORITHM BASED ON WIDELY CHAOTIC 5D SYSTEM...

引用

Proceedings of the 2025 4th International conference on Cryptography, Network Security and Communication Technology

作者： Puquan Cao Yanwei Zhu Luozhi Zhang College of Computer Science & Cyber Security Chengdu University of Technology Chengdu Sichuan China

ISBN: (纸本)9798400712623

Addressing the complexity of existing image encryption procedures, suboptimal computational performance, limited key space, and poor attack resistance. In this paper, a novel image encryption approach combining Arnold's cat map, DNA coding and five-dimensional multi-stable hyperchaotic system is proposed. the method utilizes the five-dimensional multi-stable hyperchaotic system to generate multiple pseudo-random sequences and first applies the Arnold cat map to process the original image. Subsequently, the data is converted into DNA sequences and undergoes appropriate operations to achieve encryption. Experimental results indicate that the presented method offers notable improvements in both encryption efficiency and security, providing a new and effective solution for image encryption.

关键词： DNA sequence operation

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Cryptographic image Security Using AES-XOR Approach

Cryptographic Image Security Using AES-XOR Approach

引用

Sentiment Analysis and Deep Learning (ICSADL), International conference on

作者： Santhosh B Kushmitha V Samhita Bhat Satyaki Mondal V Joshitha Dept. of Electronics and Telecommunication Dayananda Sagar College of Engineering Bangalore India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

关键词： Histograms data privacy Teleconferencing Sensitivity Computational modeling Surveillance Streaming media Generators encryption Standards

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EnigmaArt: Dual image encryption and compression via Autoencoding and Pixel Conversion 4th

EnigmaArt: Dual Image Encryption and Compression via Autoe...

引用

4th International conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2024

作者： Tiwari, Naveen Kumar Rajput, Shyam Singh Yadav, Aditya National Institute of Technology Patna Bihar Patna India Rajkiya Engineering College Kannauj UP Kannauj India

ISBN: (纸本)9783031837890

Securing sensitive visual data is essential in the digital age. Our research presents a sophisticated model of image encryption that combines RNA pixel conversion with an autoencoder. A convolutional neural network (CNN) is used for efficient feature extraction. Convolutional encoding and RNA pixel conversion, which map pixels to RNA sequences (Adenine, Cytosine, Guanine, Uracil) enabling stronger encryption, are the model’s primary innovations. By guaranteeing that every encryption instance is distinct, this dynamic technique strengthens security. Our approach ensures security and picture integrity by demonstrating robust encryption capabilities with minimum reconstruction loss (0.0617), as tested on the MNIST dataset. Furthermore, the encryption procedure is optimized by a fractional order optimizer, FGL_Adam, which incorporates weight decay, learning rate modifications, and a security improvement factor. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Enhancing the Compressed Video Quality through a Neural Network Approach

Enhancing the Compressed Video Quality through a Neural Netw...

引用

Sentiment Analysis and Deep Learning (ICSADL), International conference on

作者： Karthick Panneerselvam K. Rajalakshmi P. Sornalatha Department of Computer Science & Engineering KPR Institute of Engineering and Technology Uthupalayam Tamil Nadu India Department of MCA CMR Institute of Technology Bengaluru Karnataka India Department of Computer Applications Alagappa University Karaikudi Tamil Nadu India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

关键词： Video coding Recurrent neural networks PSNR image coding Superresolution Graphics processing units Video compression Generative adversarial networks Encoding Standards

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Lightweight security Mechanism for IoT Applications using Substitution-Box

Lightweight security Mechanism for IoT Applications using Su...

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AI in Cybersecurity (ICAIC), International conference on

作者： Fozia Hanif Rehan Shams Urooj Waheed Department of Mathematics University of Karachi Karachi Pakistan Department of Telecommunication Sir Syed University of Engineering and Technology Karachi Pakistan Department of Computer Science DHA Suffa University Karachi Pakistan

ISBN: (数字)9798331518882

ISBN: (纸本)9798331518899

关键词： Wireless communication Ciphers Wireless sensor networks throughput encryption Sensors Security Internet of things S Box Radiofrequency identification

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