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9th International Conference on Intelligent Informatics and BioMedical sciences, ICIIBMS 2024

作者： Xue, Qingshui She, Huitong Shanghai Institute of Technology School of Computer Science and Information Engineering Shanghai China

ISBN: (纸本)9798350363043

As the Internet and information technology advance, safeguarding user personal data is critical. Traditional registration and key storage methods pose security risks like data breaches and centralized vulnerabilities. This paper proposes a solution integrating elliptic curve encryption, multi-party collaboration, blockchain, and secret sharing. The system divides roles among users, blockchain systems, and regulators, using secure channels and distributed storage to manage keys and protect user information. Experimental results show high effectiveness with a 98% registration success rate, 95% key recovery rate, and zero information leaks. This approach enhances system stability and user satisfaction while ensuring privacy in online services. © 2024 IEEE.

关键词： information leakage

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Security and Privacy Preserving GDPR-Compliant Scheme Resisting in Rendering False Data 15

Security and Privacy Preserving GDPR-Compliant Scheme Resist...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Dutta, Mou Dhal, Subhasish Indian Institute of Information Technology Guwahati Computer Science and Engineering Guwahati India

ISBN: (纸本)9798350370249

The protection of personal data has grown to be a top priority around the world. The General Data Protection Regulation (GDPR) enables the data subjects (DS) to get back the control of their personal information, which is usually managed and processed by Service Providers (SP). Therefore, it is to check whether a service by SP is GDPR compliant. Manual verification is not feasible as a lot of data are being generated over time by a DS. An automated process may help. We explored a recent such automated tool, which allows the SP to provide requested data to a User (U) only if the DS has the consent for this transaction. However, a malicious SP can alter the data as the correctness of the received data is not being verified. In this paper, we have addressed this problem and proposed a GDPR compliant scheme that ensures the correctness of the received data. We simulate our proposed scheme using the well-known Automated Verification of Internet Security Protocols and Application (AVISPA) verification tool, which illustrates that the proposed scheme is safe. We compare the performance of our proposed scheme with the existing scheme to ensure its acceptance in real life. © 2024 IEEE.

关键词： Differential privacy

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Self-attention Handwriting Generative Model 24

Self-attention Handwriting Generative Model

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2024 SIGGRAPH Asia 2024 Posters, SA 2024

作者： Wang, Yu-Chiao Hsieh, Tung-Ju Chiang, Pei-Ying Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9798400711381

Recent advancements in font generation models include GANs, diffusion models, and transformers. This study introduces a GAN-based model, zi2zi self-attention, which enhances the zi2zi model by incorporating Residual Blocks (ResNet Block) and Self-Attention Layers in the encoder and decoder. These enhancements improve the ability to capture complex font details, mimicking the writer's style while preserving the source image's content. The study also introduces Perceptual Loss, using high-level features from the VGG-19 network to improve visual consistency and quality. The Adam optimizer with appropriate learning rates and Beta parameters is employed to enhance convergence speed and stability. For comparison, four other mainstream models are evaluated: MX-Font, CF-Font, SDT, and Font-Diffuser. These models differ from zi2zi in their focus on extracting content characters and writing style features rather than solely using adversarial networks. Experimental results show the potential and effectiveness of zi2zi-Self-Attention in generating high-quality, visually appealing handwritten fonts. © 2024 Copyright held by the owner/author(s).

关键词： Gallium nitride

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A new framework for GNSS spoofing detection based on signal phase and structure 4

A new framework for GNSS spoofing detection based on signal ...

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4th International Conference on Electronic information engineering and computer Communication, EIECC 2024

作者： Xia, Na Li, Jiacheng Du, Huazheng Jing, Shuhao Hefei University of Technology School of Computer Science and Information Engineering Hefei China

ISBN: (纸本)9798331534622

Spoofing interference casts significant threat to the GNSS receivers making the enhancement of spoofing detection capability a crucial issue. Detection performance of traditional SQM method encounters evident degradation in interference process. Utilizing phase feature and specific structure of spoofing signal, a new spoofing detection framework has been developed to determine the existence of interference. Preliminary experimental results in TEXBAT indicate that this method owns great potential in spoofing detection, maintaining stability and accuracy in different stages of interference. © 2024 IEEE.

关键词： Global positioning system

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Bipolar interval-valued fuzzy set in graph and hypergraph settings

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Journal of Intelligent and Fuzzy Systems 2023年第2期44卷 1755-1767页

作者： Gong, Shu Hua, Gang School of Information and Control Engineering China University of Mining and Technology Xuzhou China Department of Computer Science Guangdong University Science and Technology Dongguan China

Graphs and hypergraphs are popular models for data structured representation. For example, traffic data, weather data, and animal skeleton data are all described by graph structures. Interval-valued fuzzy sets change the membership function of general fuzzy sets from single value functions to interval-valued functions, and thus describe the fuzzy attributes of things in terms of fuzzy intervals, which is more in line with the characteristics of fuzzy objectives. This paper aims to define the bipolar interval-valued fuzzy hypergraph to reveal the inner relationship of fuzzy data, and give some characterizations of it. The characteristics of bipolar interval-valued intuitionistic fuzzy hypergraph and bipolar interval-valued Pythagorean fuzzy hypergraph are studied. In addition, we discuss the characteristics of the bipolar interval-valued fuzzy threshold graph. Finally, some instances are presented as the applications of bipolar interval-valued fuzzy hypergraphs. © 2023 - IOS Press. All rights reserved.

关键词： Membership functions

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Predicting Genetic Disorders: A Link Mining Approach 2

Predicting Genetic Disorders: A Link Mining Approach

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Sen, Madhura Rajasekaran, Rajkumar Jayaram Reddy, A. Govinda, K. Vellore Institute of Technology School of Computer Science and Engineering Vellore India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350306415

Genetic diseases are conditions caused by a spontaneous alteration or mutation in an individual's DNA. People can inherit genetic disorders from parents, which means they are born with them, even if they are not initially noticeable. On the other hand, some illnesses are not inherited and arise due to disease-causing mutations occurring during cell division. In link mining, link prediction is a crucial task. Based on attribute information and observed existing link information, link prediction predicts if there will be a link between two nodes. Link prediction is applicable not just in the sphere of social networks but also in other fields. This project primarily aims to forecast a person's probability of being diagnosed with a genetic condition. To accomplish this, elements such as the person's family history, the environment in which they live, and a variety of others will be considered. The likelihood of a person being diagnosed with a specific genetic condition can be predicted using the Firefly algorithm. If a person is genetically connected to someone having a given ailment, they are more likely to be diagnosed. Pollution, radioactive radiation, and other environmental factors may also affect the disease's incidence. Considering these factors, we suggest a method for determining the likelihood of a person being diagnosed via link prediction. © 2024 IEEE.

关键词： firefly algorithm genetic disorders healthcare link prediction social network analysis

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Biological Profile Estimation of the Human Skeleton Based Forensic Identification Using Deep Learning Image Classification 5

Biological Profile Estimation of the Human Skeleton Based Fo...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Dutta, Sriparna Keerthana, R. Shekar, D Chandra Kumar, S. Satheesh Institute of Aeronautical Engineering Computer Science and Information Technology Hyderabad Dundigal India

ISBN: (纸本)9798331518097

This research study proposes an innovative methodology for the automated estimation of biological profiles through deep learning techniques, with a particular focus on the classification of age and gender derived from chest X-ray imaging. Utilising Convolutional Neural Networks (CNNs) within the TensorFlow/Keras framework, this investigation confronts the inherent limitations associated with traditional forensic anthropology, such as examiner bias, protracted processing durations, and the variability encountered in instances of poorly preserved skeletal remains. The proposed system capitalises on chest X-rays to extend the analytical reach of skeletal assessments beyond the typically examined osseous structures, attaining an impressive 96% accuracy in gender classification alongside negligible error rates in age estimation. These findings highlight the capacity of CNNs to effectively extract and scrutinise intricate anatomical features, thereby facilitating accurate forensic profiling. In contrast to conventional methodologies, this paradigm significantly reduces the necessity for human involvement, presenting a more objective, efficient, and scalable alternative for forensic identification. The incorporation of this system into a user-centric interface enhances its applicability in practical contexts, further illustrating its practical significance. Although this study reveals considerable advancements, subsequent endeavours will concentrate on augmenting the diversity of the dataset and investigating sophisticated architectures to improve generalisability and performance metrics. This research accentuates the transformative potential inherent in AI-driven methodologies within forensic science and medical imaging, establishing a solid foundation for future innovations in these domains. © 2024 IEEE.

关键词： Convolutional neural networks

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A Dehazing Method Based on Fog Density Fusion of Dark and Bright Channel Images 9

A Dehazing Method Based on Fog Density Fusion of Dark and Br...

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9th International Conference on Intelligent Informatics and BioMedical sciences, ICIIBMS 2024

作者： Yang, Delong Shanghai Institute of Technology School of computer science and Information Engineering Shanghai China

ISBN: (纸本)9798350363043

To address issues of imprecise transmission fusion and unsmooth transitions in regions with varying depths of field, as well as color distortion in large white areas after dehazing, this paper proposes a dehazing method based on fog density fusion of dark and bright channel images. First, the FADE (Fog Aware Density Evaluator) method is used to extract the fog density map of the hazy image. Then, the transmission rates of the dark and bright channels are computed, and each pixel's fog density is used as a weight to fuse the two transmission rates on a pixel-wise basis. Subsequently, the average brightness of the brightest part of some pixels in dense fog areas is selected as the atmospheric light value. Finally, the haze-free image is restored using the atmospheric scattering model. Experimental results show that the improved dehazing method effectively preserves pixel edge details, achieves smooth transmission transitions in regions with varying depths of field, and significantly reduces halo effects. © 2024 IEEE.

关键词： Demulsification

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AR-Light: Enabling Fast and Lightweight Multi-User Augmented Reality via Semantic Segmentation and Collaborative View Synchronization

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IEEE Transactions on computers 2025年第6期74卷 2073-2086页

作者： Wen, Yu Shah, Aamir Bader Cao, Ruizhi Zhang, Chen Chen, Jiefu Wu, Xuqing Xie, Chenhao Fu, Xin University of Houston Department of Electrical and Computer Engineering HoustonTX77204 United States Beihang University School of Computer Science and Engineering Beijing100191 China University of Houston Department of Information Science Technology HoustonTX77204 United States

Multi-user Augmented Reality (MuAR) allows multiple users to interact with shared virtual objects, facilitated by exchanging environment information. Current MuAR systems rely on 3D point clouds for real-world analysis, view synchronization, object rendering, and movement tracking. However, the complexity of 3D point clouds leads to significant processing delays, with approximately 80% of overhead in commercial frameworks. This hampers usability and degrades user experience. Our analysis reveals that maintaining the facing side of the real-world scene in a stable environment provides sufficient information for virtual object placement and rendering. To address this, we introduce a lightweight quadtree structure, representing 2D scenes through semantic segmentation and geometry, as an alternative to 3D point clouds. Additionally, we propose a novel correction method to handle potential shifts in virtual object placement during view synchronization among users. Combining all designs, we implement a fast and lightweight MuAR framework named AR-Light and test our framework on commercial AR devices. The evaluation results on real-world applications demonstrate that AR-Light can achieve high performance in various real-world scenes while maintaining a comparable virtual object placement accuracy. © 1968-2012 IEEE.

关键词： Semantic Segmentation

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Ramp Progressive Secret Image Sharing using Ensemble of Simple Methods 14

Ramp Progressive Secret Image Sharing using Ensemble of Simp...

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14th International Conference on computer and Knowledge engineering, ICCKE 2024

作者： Mokhtari, Atieh Taheri, Mohammad Department of Computer Science and Engineering and Information Technology Shiraz University Shiraz Iran

ISBN: (纸本)9798331511272

This paper reviews the limitations of traditional Secret Image Sharing (SIS) methods and recent advancements such as PSIS, RPSIS, and SSIS, and presents an optimized and practical combinatorial method for secret image sharing by ensemble of simple methods. In this approach, a color or grayscale image is divided into n shares, each of which is individually meaningless. The image is reconstructed through XOR operations between corresponding pixels in different shares. The main innovation of this method is the introduction of two thresholds, k1 and k2. This scheme is characterized by parameters (k1, k2, n), where having fewer than k1 shares reveals no information about the original image, while between k1 and k2 shares, the image quality progressively improves and reaches near-complete reconstruction. Ultimately, with k2 or more shares, the image can be recovered in its full resolution. This method allows for customization of the image quality improvement rate between k1 and k2 and addresses the limitations of previous designs regarding the selection of k1, k2, and n values. Its flexibility in providing suitable models based on specific user needs makes this method appropriate for various applications in secret image sharing. ©2024 IEEE.

关键词： Progressive Recovery Progressive Secret Image Sharing Ramp Secret Image Sharing Secret Image Sharing Secret Sharing Visual Cryptography

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