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

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

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

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4th International conference on Advanced Network Technologies and Intelligent Computing-ANTIC-Annual

作者： Tiwari, Naveen Kumar Rajput, Shyam Singh Yadav, Aditya Natl Inst Technol Patna Patna Bihar India Rajkiya Engn Coll Kannauj Kannauj UP India

ISBN: (纸本)9783031837890;9783031837906

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.

关键词： image encryption Autoencoder Fractional Optimizer

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Cryptographic image Security Using AES-XOR Approach 4

Cryptographic Image Security Using AES-XOR Approach

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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...

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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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Dictionary-Based BPT compression with Trimodal encryption for Efficient Fiber-Optic data Management and Security 4th

Dictionary-Based BPT Compression with Trimodal Encryption fo...

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4th International conference on Smart Systems: Innovations in Computing, SSIC 2023

作者： Alapatt, Bosco Paul Poonia, Ramesh Chandra Singh, Chandraketu Delhi NCR India

ISBN: (纸本)9789819736898

Fiber-optic transmission systems are capable of carrying tens of terabits per second of traffic and thereby form the core infrastructure for all Internet-based services and applications. While fiber-optic communication provides rapid data transfer, it faces the challenge of managing the substantial data volumes generated, stored, or transmitted. In the realm of fiber-optic communication, data interception is straightforward, necessitating robust security measures. One effective solution is compression-based encryption, which combines security with data compression benefits. encryption safeguards data by transforming it into ciphertext during transmission, rendering it unreadable to attackers without knowledge of the encryption method. data compression enhances bandwidth efficiency, enabling the efficient transmission of large data volumes using limited bandwidth. In the event of data compromise, attackers must grasp both compression and encryption methods to decipher the information, adding an additional layer of security. In this paper, an encoding technique named the Bounded Probability-Based Textual data compression (BPT) algorithm is introduced with trimodal encryption method for securing the short textual data while transferring from source to the destination. the BPT algorithm creates a codeword using a dictionary that assigns binary codes according to character occurrence probabilities in the input data. To decompress, the coding table must be transmitted alongside the compressed data. the trimodal encryption is used as a second tier for securing the data that was compressed using BPT algorithm. the trimodal encryption employs three encryption methods, and data is encrypted using one of these methods during transmission to the destination. the BPT algorithm’s performance is evaluated using benchmark textual datasets from the Calgary Corpus and the Canterbury Corpus. the experimental results demonstrate the unique characteristics of the BPT algorithm, includin

关键词： Bandwidth compression

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Lightweight security Mechanism for IoT Applications using Substitution-Box 4

Lightweight security Mechanism for IoT Applications using Su...

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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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Chaotic image encryption method based on Zigzag scrambling and DNA coding 4

Chaotic image encryption method based on Zigzag scrambling a...

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4th International conference on Frontiers Technology of Information and Computer, ICFTIC 2022

作者： Liu, Zhen Zhu, Donglin Zhou, Changjun Zhang, Wenyu College of Mathematics and Computer Science of Zhejiang Normal University Zhejiang province Jinhua China College of Faculty of Information Science and Engineering Ocean University of China Shandong province Qingdao China

ISBN: (纸本)9798350321951

In the process of using the network, data security needs to be considered. image, as an important part of data, also needs to be considered. image encryption play an important role in protecting users' confidential data. this paper design a new image encryption algorithm based on chaotic sequence, zigzag scrambling, DNA coding. the experimental results indicate that this method can effectively encrypt data and ensure data security. © 2022 IEEE.

关键词： DNA

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image compression scheme based on region of interest recognition 4

Image compression scheme based on region of interest recogni...

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4th International conference on Electronic Communication, Computer Science and Technology, ECCST 2024

作者： Wu, Dawei Bai, Enjian College of Information Science and Technology Donghua University Shanghai201620 China

With the development of networks, many fields now demand higher quality in specific image areas, such as main characters in photos, lesion areas in medical images, and features in remote sensing. At the same time, these fields need to manage data storage and transmission effectively for subsequent analysis and application. In order to meet the demand for image compression in modern society, this paper proposes an image compression scheme based on region of interest (ROI) recognition, dividing images into ROI and non-ROI regions and processing them with lossless and lossy compression, respectively, to improve efficiency and ensure ROI quality. the scheme uses the object detection network YOLOv4 to recognize the ROI of the image, designs an image block difference transformation to transform the image pixels into smaller values, designs a lossless DC encoding for the ROI of the image based on the difference between adjacent pixels, and designs a lossy DC encoding with quantization coding for the non-ROI of the image. Experimental analysis of uncompressed images shows the scheme effectively enhances compression efficiency while maintaining ROI quality, proving its practical value. © Published under licence by IOP Publishing Ltd.

关键词： Pixels

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Improving image compression Performance by Spatial-Channel Context Adaptive Model 4

Improving Image Compression Performance by Spatial-Channel C...

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4th International conference on Electronic Communication and Artificial Intelligence, ICECAI 2023

作者： Wang, Hao Wang, Huifen Xue, Junda Lu, Enmin Wang, Hanming Wu, Zijun Song, Yunlong Institute of Big Data and Artificial Intelligence China Telecom Corporation Limited Beijing Research Institute Beijing China

ISBN: (纸本)9798350314496

the significance of enhancing image compression efficiency for machine vision, analysis, and comprehension tasks has gained increasing recognition. In response to this need, we propose and implement a novel method called ELIC (Efficient Learned image compression with Unevenly Grouped Space-Channel Contextual Adaptive coding) to achieve high compression efficiency. Our method is evaluated on the classic Openimage V6 Common Test Condition (CTC) eval datasets, and its performance is compared to baseline methods for machine vision tasks. the results of our study demonstrate a substantial enhancement in compression efficiency, suggesting that the ELIC technique holds promise for pushing the boundaries of state-of-the-art visual compression for vision tasks. Furthermore, we believe that our approach can promote the application of learning-based image compression. © 2023 IEEE.

关键词： image compression

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Color image encryption Using Genetic Recombination With Tent Mapping Based Time-Delay Chaotic 4

Color Image Encryption Using Genetic Recombination With Tent...

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4th International conference on Computer Graphics, image, and Virtualization, ICCGIV 2024

作者： Xu, Yaoqun Liu, Jiaoyang Institute of System Engineering Harbin University of Commerce Harbin150028 China School of Computer and Information Engineering Harbin University of Commerce Harbin150028 China

ISBN: (纸本)9781510683242

As the form of information transmission has shifted from text to images in recent years, the in-crease in information dimension has led to a growing interest in secure and efficient encryption algorithms. this paper proposes a chaotic system that combines tent mapping and a time-delay chaotic neural network, and it extracts a single neuron to test the system's chaotic properties and stability. On this basis, the randomness test of the chaotic sequence generated by the system is conducted to ensure that the new chaotic system can maintain the chaotic state more effectively. In addition, genetic recombination compensates for the restriction that DNA code cannot be confounded and diffused during the encryption procedure. In this paper, chaotic sequences are applied to genetic recombination and DNA coding, and an algorithm for image encryption is proposed. the data indicate that the algorithm has excellent anti-attack capabilities. In addition, the algorithm has passed the NIST and TestU01 randomness evaluations, guaranteeing its sensitivity and randomness. therefore, the algorithm is secure and can be used to encrypt color images. © 2024 SPIE.

关键词： Gene encoding

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