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Anonymous Authentication Without Home Server in Mobile Roaming Networks

Chinese Journal of Electronics 2023年第2期22卷 382-386页

作者： Chunlin Jiang Weijia Jia Ke Gu Ning Xu School of Information Science and Engineering Central South University Changsha China China Standard Software Co. Ltd Shanghai China Department of Computer Science City University of Hong Kong Kowloon Hong Kong

In this paper, we propose an anonymous authentication protocol based on group signature under Canetti-Krawczyk (CK) model for mobile roaming networks. The protocol involves only a mobile user and the user's visited server, without the involvement of the user's home server until the user's identity (ID) needs to be revealed. In order to reduce the computational burden on the mobile terminals, the protocol gives a method that minimizes expensive pairing operations. Then, its performance as well as efficiency is analyzed. It is shown that the proposed protocol greatly reduces the average authentication latency while security and anonymity are still preserved. Therefore, it can be applicable in practical applications.

关键词： Technological innovation Protocols Computational modeling Authentication Servers Security Research and development

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Inner-approximate Reachability Computation via Zonotopic Boundary Analysis

arXiv

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arXiv 2024年

作者： Ren, Dejin Liang, Zhen Wu, Chenyu Ding, Jianqiang Wu, Taoran Xue, Bai Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China College of Computer Science and Technology National University of Defense Technology Changsha China Department of Electrical Engineering and Automation Aalto University Espoo Finland

Inner-approximate reachability analysis involves calculating subsets of reachable sets, known as inner-approximations. This analysis is crucial in the fields of dynamic systems analysis and control theory as it provides a reliable estimation of the set of states that a system can reach from given initial states at a specific time instant. In this paper, we study the inner-approximate reachability analysis problem based on the set-boundary reachability method for systems modelled by ordinary differential equations, in which the computed inner-approximations are represented with zonotopes. The set-boundary reachability method computes an inner-approximation by excluding states reached from the initial set’s boundary. The effectiveness of this method is highly dependent on the efficient extraction of the exact boundary of the initial set. To address this, we propose methods leveraging boundary and tiling matrices that can efficiently extract and refine the exact boundary of the initial set represented by zonotopes. Additionally, we enhance the exclusion strategy by contracting the outer-approximations in a flexible way, which allows for the computation of less conservative inner-approximations. To evaluate the proposed method, we compare it with state-of-the-art methods against a series of benchmarks. The numerical results demonstrate that our method is not only efficient but also accurate in computing inner-approximations. Copyright © 2024, The Authors. All rights reserved.

关键词： Ordinary differential equations

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Polarization Correction using Physics-guided Foundation Model for Photon-Counting CT

Polarization Correction using Physics-guided Foundation Mode...

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IEEE Symposium on Nuclear science (NSS/MIC)

作者： X. Yu W. Qin T. Zhong Q. Wu M. Su W. Wang X. Ji G. Quan Y. Chen X. Lai School of Biomedical Engineering ShanghaiTech University Shanghai China School of Computer Science and Engineering Southeast University Nanjing China College of Software Engineering Southeast University Nanjing China CT RPA Department United Imaging Healthcare Shanghai China

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

Photon-counting computed tomography (PCCT) represents a paradigm-shift advancement in CT technology. However, a significant challenge in PCCT is the polarization effect in photon-counting detectors (PCDs), especially in cadmium-based PCDs, which generate instable counting rate and inaccurate material decomposition results. In this paper, we introduce a polarization spectrum response model and propose a polarization correction method based on a physics-guided foundation model for photon-counting CT. Our approach is designed to accurately address the complexities of time-varying and dose-dependent polarization in PCDs. Preliminary results demonstrate accurate material decomposition that is free of significant band artifacts with proper polarization correction, underscoring the potential benefits in PCCT image quality.

关键词： Image quality Polarization Microwave integrated circuits Accuracy Semiconductor detectors Computed tomography Computational modeling

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The Performance Analysis of Distributed Denial of Service Attacks in Wireless Networks

The Performance Analysis of Distributed Denial of Service At...

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International Conference on Futuristic Technologies (INCOFT)

作者： Trapty Agrawal R Raghavendra K. Ranjith Singh Rajiv Gandhi N Dharmesh Dhabliya Jitendra Kumar Katariya Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Indi Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore Karnataka India Department of Computer Science Karpagam Academy of Higher Education Coimbatore Department of Civil Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Information Technology Vishwakarma Institute of Information Technology Pune Maharashtra India Department of Computer Science & Application Vivekananda Global University Jaipur India

Complete studies paper that examines the outcomes that malicious 0.33-celebration actors will have on Wi-Fi networks via dispensed denial of carrier (DDoS) attacks. This paper explores the available numerous assault models and the potential countermeasures that may be applied if you want to mitigate the damage due to such assaults. In addition, this paper focuses on the capability blessings related to deploying preventative measures to lessen the impact of such assaults. Moreover, the paper investigates existing attack trends. It affords an outline of the safety techniques to be had for limiting the harm caused by DDoS attacks in wireless networks. By comparing and analyzing the performance of diverse protection mechanisms, this paper offers an evidenceprimarily based evaluation of the effectiveness of DDoS attack safety answers. ultimately, this paper concludes with the aid of supplying recommended measures for strengthening and ensuring the safety of Wi-Fi networks against malicious actors.

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DPFedSAM-Meas: Comparison Of Differential Privacy Federated Learning In Medical Image Classification

DPFedSAM-Meas: Comparison Of Differential Privacy Federated ...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Shunrong Jiang Zhi Wang Zixuan He Yonggang Li Xiaofan Li Haotian Chi Xiaojiang Du School of Computer Science China University of Mining and Technology Xuzhou China Jiangsu Jingchuang Electric CO. LTD School of Automation and Software Engineering Shanxi University Taiyuan China Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken NJ USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Machine learning is widely used in medical image classification tasks. However, medical images often exhibit uneven distribution and high sensitivity to noise. A feasible solution involves using federated learning (FL) with differential privacy (DP), a distributed training method that protects patient privacy. In this work, many studies have proposed improved solutions for localized differential-private federated learning (DP-FL) frameworks. However, these studies are isolated, which would be detrimental to privacy practitioners in designing and using the algorithms. To provide a comprehensive analysis of these algorithms, we propose DPFedSAM-Meas, as a framework for comprehensive utility analysis of DP-FL. In this framework, we employed the state-of-the-art federated learning framework FedSAM. Moreover, we categorize DP algorithms into Laplace DP and Gaussian DP by the underlying DP mechanisms, and into Gradient DP and Parameter DP by the DP position in FL train. DPFedSAM-Meas allows a comparative analysis of these four DP techniques, measuring their model utility, privacy leakage, and overhead when FL uses different network structures. Finally, we evaluate DPFedSAM-Meas on datasets of Pneumonia, Blood, and Path, aiming to investigate the performance of different DP techniques on mainstream deep learning algorithms, including Convolutional Neural Networks (CNN) and Vision Transformers (ViT).

关键词： Training Privacy Differential privacy Sensitivity Pneumonia Federated learning Transformers Convolutional neural networks Biomedical imaging Image classification

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Multi-task Scheduling Algorithm Based on Self-adaptive Hybrid ICA–PSO Algorithm in Cloud Environment 8th

Multi-task Scheduling Algorithm Based on Self-adaptive Hybri...

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8th International Workshop on Soft Computing applications, SOFA 2018

作者： Tabrizchi, Hamed Kuchaki Rafsanjani, Marjan Balas, Valentina Emilia Department of Computer Science Faculty of Mathematics and Computer Shahid Bahonar University of Kerman Kerman Iran Department of Automatics and Applied Software Faculty of Engineering Aurel Vlaicu University of Arad Arad Romania

ISBN: (纸本)9783030521899

Cloud is a new concept in Internet technology and has brought many benefits, particularly, in the field of computing. Cloud has changed how on-demand resources are allocated to the different user requests and has provided more optimal resource utilization. Tasks (user requests) have different kinds, including deadline-based tasks having time-related limitations. This kind of task has various parameters and scheduling them is more challenging than scheduling the individual tasks. In this regard, many papers have been published according to these parameters. The objective of this paper is to propose a novel self-adaptive hybrid ICA–PSO algorithm for dealing with associate multi-task scheduling problem. To improve the exploration, two algorithms, namely, the imperialist competitive algorithm (ICA) and particle swarm optimization (PSO) were combined in this study. The results of the present study outperform those of the existing mechanisms. © 2021, Springer Nature Switzerland AG.

关键词： Scheduling algorithms

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AI-Enhanced Multi-Cloud Security Management: Ensuring Robust Cybersecurity in Hybrid Cloud Environments

AI-Enhanced Multi-Cloud Security Management: Ensuring Robust...

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Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

作者： Srimathi. J K. Kanagasabapathi Kirti Mahajan Shahanawaj Ahamad E. Soumya Shivangi Barthwal Department of Information Technology KPR College Of Arts Science And Research Arasur Covai Computer Science and Technology Karpagam College of Engineering Coimbatore Department of Information Technology Institute of Management & Entrepreneurship Development Bharati Vidyapeeth Deemed University Pune Department of Software Engineering College of Computer Science and Engineering University of Hail Hail City Saudi Arabia Department of Computer Science and Engineering St. Martins Engineering College Secunderabad Telangana Department of Electronics & Communication Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

The complex landscape of multi-cloud settings is the result of the fast growth of cloud computing and the ever-changing needs of contemporary organizations. Strong cyber defenses are of fundamental importance in this setting. In this study, we investigate the use of AI in hybrid cloud settings for the purpose of multi-cloud security management. To help businesses improve their productivity and resilience, we provide a mathematical model for optimal resource allocation. Our methodology streamlines dynamic threat assessments, making it easier for security teams to efficiently priorities vulnerabilities. The advent of a new age of real-time threat response is heralded by the incorporation of AI-driven security tactics. The technique we use has real-world implications that may help businesses stay ahead of constantly changing threats. In the future, scientists will focus on autonomous security systems, interoperability, ethics, interoperability, and cutting-edge AI models that have been validated in the real world. This study provides a detailed road map for businesses to follow as they navigate the complex cybersecurity landscape of multi-cloud settings, therefore promoting resilience and agility in this era of digital transformation.

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Classification of Plants Leave Using Image Processing and Neural Network 8th

Classification of Plants Leave Using Image Processing and Ne...

引用

8th International Workshop on Soft Computing applications, SOFA 2018

作者： Bagherinezhad, Hashem Kuchaki Rafsanjani, Marjan Balas, Valentina Emilia Koles, Ioan E. Department of Computer Science Faculty of Mathematics and Computer Shahid Bahonar University of Kerman Kerman Iran Department of Automatics and Applied Software Faculty of Engineering Aurel Vlaicu University of Arad Arad Romania

ISBN: (纸本)9783030521899

Plants are one of the most widely used resources for humans in different fields. Therefore, the distinction between the plant species is important and it is referred to as the plant detection system. Until now, this task has been done by the expert botanists which is an overwhelming and time consuming task. Moreover, there is a lack of the memory and the human fault, so the researchers endeavored to solve these disadvantages using the AI algorithms. For this goal, in this paper, a system is proposed that includes four phases: pre-processing, feature extraction, training, and test. In this method, we use the combination of the useful features of the leave shape, the leave texture, the leave color, and we provide a method for the classification of a number of the plant species. Finally, the feature vectors will be created and then, the classification is performed by using feed-forward back-propagation multi-layer perceptron artificial neural network algorithm. Then, the results of this method compare with other methods. The obtained results show the high accuracy of this method for a large number of the species in different conditions (such as pests, season changes and lighting). © 2021, Springer Nature Switzerland AG.

关键词： Feature extraction

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The Way to Check the Reliability Test in Smart Grids for the Smart Protection System

The Way to Check the Reliability Test in Smart Grids for the...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Hannah Jessie Rani R Manish Kumar Goyal Awakash Mishra Department of Electrical and Elceltronics Engineeirng Faculty of Engineering and Technology JAIN (Deemed to be University) Bangalore India Department of Computer Science & Application Vivekananda Global University Jaipur India Engineering Department Maharishi University of Information Technology Uttar Pradesh India

The complex operation of contemporary power systems is closely linked to the widespread integration of computer networks, or cyber networks. These applications fall into two general categories: direct and indirect interdependencies, which are the result of how they communicate with power networks. Past studies explored the area of direct interdependencies in cyber-power networks and presented a state mapping-based model that was carefully designed to assess its impact on power system dependability. The investigation of indirect relationships between cyber and electricity networks is the new emphasis of this article. A wide range of applications involving indirect interdependencies in modern power systems are examined, laying the foundation for the release of a model that is based on state updating. This model is carefully crafted to provide a numerical evaluation of cyber-power networks' dependability in the face of indirect interdependencies. Two separate models are used to maximize data communication inside the cyber network and minimize load limitation in the power network, respectively, in order to maximize the functioning of these integrated networks. In order to demonstrate the efficacy of the suggested solution model, the research focuses on a high-voltage converter equipped with both protection and monitoring devices. By taking a comprehensive approach, the research makes a substantial contribution to a deeper understanding of the complex interactions between cyber and electricity networks, providing priceless insights for enhancing the dependability of these interconnected systems.

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Research on Seedling Grading of Platycladus Orientalis Based on Fuzzy C-Means Clustering Algorithm Improved by Genetic Sparrow Family Search Optimization

SSRN

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SSRN 2023年

作者： Liu, Yang Zhou, Juan Wang, Juan Di, Bao Wang, Chao Ren, ZhenHui College of Mechanical and Electrical Engineering Hebei Agricultural University Baoding071001 China Department of Computer Application Engineering Hebei Software Institute Baoding071000 China College of Horticulture Hebei Agricultural University Baoding071001 China College of Information Science and Technology Hebei Agricultural University Baoding071001 China

Platycladus orientalis has high ecological and economic value, but the quality of Platycladus orientalis seedlings varies greatly. The original quality grading standard is relatively simple and the grading boundary is not clear. It is of great significance to use the in-situ Electrical Impedance Spectroscopy (EIS) technique for nondestructive testing of Platycladus orientalis roots and the improved fuzzy C-means clustering algorithm for scientific and accurate grading of Platycladus orientalis seedlings combined with morphological *** a result, five parameters were found reflecting the quality of Platycladus orientalis seedlings, including phase angle at 4000Hz and tangent value at 400kHz, which could reflect the quality of roots. An Fuzzy C-means (FCM) clustering algorithm improved by genetic sparrow family search optimization (GSFS-FCM) was proposed. Through the test of standard functions and typical datasets, it was found that the number of clusters of the algorithm could be determined automatically. Although the running time is increased, the number of iterations is reduced by more than 12%, and the clustering error rate is reduced by more than 8%. Finally, eight months old Platycladus orientalis seedlings were divided into six grades with the GSFS-FCM *** the present study it can be concluded that among the Platycladus orientalis seedlings root EIS parameters measured by the instrument in situ, phase angle at 4000Hz and tangent value at 400kHz can be used to represent the quality of the roots. GSFS-FCM algorithm can effectively and automatically grading the seedlings of Platycladus orientalis without specifying the number of clusters. The algorithm has fewer iterations and higher accuracy. © 2023, The Authors. All rights reserved.

关键词： Grading

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