检索结果-内蒙古大学图书馆

8th International Conference on computer and Communication Systems, ICCCS 2023

作者： Wu, Tong Li, Han Gao, Bo Xiong, Ke Fan, Pingyi Ben Letaief, Khaled Eng. Res. Center of Network Management Technology for High Speed Railway of Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China Beijing Jiaotong University Collaborative Innovation Center of Railway Traffic Safety Beijing100044 China Beijing Jiaotong University National Engineering Research Center of Advanced Network Technologies Beijing100044 China Tsinghua University Department of Electronic Engineering Beijing100084 China Hong Kong University of Science and Technology Department of Electrical and Computer Engineering Hong Kong Hong Kong

ISBN: (纸本)9781665456128

Ultra-wideband (UWB) is a popular technology for indoor positioning. However, non-line-of-sight (NLOS) propagation caused by human occlusion dramatically affects the accuracy of UWB-based indoor positioning. Most of the existing works focused on mitigating NLOS errors in the scenarios with building structure occlusion, but the NLOS mitigation under human occlusion has not been well addressed. To this end, this paper aims to mitigate the NLOS impact of human occlusion, and then proposes a method of NLOS mitigation to reduce NLOS ranging errors under human occlusion with low-cost UWB devices (i.e., NM-LUD). It takes a set of signal features extracted from low-cost devices as input, calculates their weights and mitigates the ranging error based on the features' weights. Experiment results on the two data sets collected by LinkTrack S and UML1 UWB devices show that the method reduces ranging error from 0.9009 m to 0.1435 m (about by 84.07%) and from 0.7466 m to 0.0792 m (about by 89.39%) respectively, which greatly mitigates the influence of NLOS caused by human occlusion. © 2023 IEEE.

关键词： Costs

来源：评论

学校读者我要写书评

暂无评论

Automated AI Research on Cyber Attack Prediction and Security Design 6

Automated AI Research on Cyber Attack Prediction and Securit...

引用

6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Madala, Ravikiran Vijayakumar, N. Nandini, N. Verma, Shanti Chandvekar, Samidha Devendra Singh, Devesh Pratap Network and Data Center Engineer Ph.D Information Technology University of Cumberlands DurhamNC United States Karpagam College of Engineering Department of Computer Science and Technology Coimbatore India Dr. Ambedkar Institute of Technology Department of Computer Science and Engineering Karnataka Bengaluru India L J University Department of Computer Application Gujarat Ahmedabad India Department of Information Technology Maharashtra New Panvel India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttrakhand Dehradun India

ISBN: (纸本)9798350304480

A fast expanding topic of study on automated AI is focused on the prediction and prevention of cyber-attacks using machine learning algorithms. In this study, we examined the research on applying machine learning algorithms to the problems of strategic cyber defense and attack forecasting. We also provided a technique for assessing and choosing the best machine learning models for anticipating cyber-attacks. Our findings show that machine learning methods, especially random forest and neural network models, are very accurate in predicting cyber-attacks. Additionally, we discovered a number of crucial characteristics, such as source IP, packet size, and malicious traffic that are strongly associated with the likelihood of cyber-attacks. Our results imply that automated AI research on cyber-attack prediction and security planning has tremendous promise for enhancing cyber-security and averting cyber-attacks. © 2023 IEEE.

关键词： automated AI research cyber-attack prediction feature correlation machine learning neural network random forest security design

来源：评论

学校读者我要写书评

暂无评论

Resource Allocation for Throughput Maximization in Cognitive Radio network with NOMA

引用

computers, Materials & Continua 2022年第1期70卷 195-212页

作者： Xiaoli He Yu Song Yu Xue Muhammad Owais Weijian Yang Xinwen Cheng School of Computer Science Sichuan University of Science and EngineeringZigong643000China Department of Network Information Management Center Sichuan University of Science and EngineeringZigong643000China School of Information Engineering South West University of Science and TechnologyMianyang621010China School of Computer and Software Nanjing University of Information Science and TechnologyJiangsu210044China Alhamd Islamic University Airport Road Quetta BalochistanPakistan

Spectrum resources are the precious and limited natural *** order to improve the utilization of spectrum resources and maximize the network throughput,this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonalmultiple access(CRN-NOMA).NOMA,as the key technology of the fifth-generation communication(5G),can effectively increase the capacity of 5G *** optimization problem proposed in this paper aims to maximize the number of secondary users(SUs)accessing the system and the total throughput in the *** the constraints of total power,minimum rate,interference and SINR,CRN-NOMA throughput is maximized by allocating optimal transmission ***,for the situation of multiple sub-users,an adaptive optimization method is proposed to reduce the complexity of the optimization ***,for the optimization problem of nonlinear programming,a maximization throughput optimization algorithm based on Chebyshev and convex(MTCC)for CRN-NOMA is proposed,which converts multi-objective optimization problem into single-objective optimization problem to *** the same time,the convergence and time complexity of the algorithm are *** analysis and simulation results show that the algorithm can effectively improve the system *** terms of interference and throughput,the performance of the sub-optimal solution is better than that of orthogonal-frequency-division-multiple-access(OFDMA).This paper provides important insights for the research and application of NOMA in future communications.

关键词： Resource allocation non-orthogonal multiple access cognitive radio network throughput maximization Chebyshev convex

来源：评论

学校读者我要写书评

暂无评论

Multi-Path Attention Inverse Discrimination network for Offline Signature Verification

引用

Intelligent Automation & Soft Computing 2023年第6期36卷 3057-3071页

作者： Xiaorui Zhang Yingying Wang Wei Sun Qi Cui Xindong Wei School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China Wuxi Research Institute Nanjing University of Information Science&TechnologyWuxi214100China Engineering Research Center of Digital Forensics Ministry of EducationJiangsu Engineering Center of Network MonitoringNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing210044China School of Automation Nanjing University of Information Science&TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of WindsorWindsorN9B 3P4Canada School of Teacher Education Nanjing University of Information Science&TechnologyNanjing210044China

Signature verification,which is a method to distinguish the authenticity of signature images,is a biometric verification technique that can effectively reduce the risk of forged signatures in financial,legal,and other business ***,compared with ordinary images,signature images have the following characteristics:First,the strokes are slim,i.e.,there is less effective ***,the signature changes slightly with the time,place,and mood of the signer,i.e.,it has high intraclass *** challenges lead to the low accuracy of the existing methods based on convolutional neural net-works(CNN).This study proposes an end-to-end multi-path attention inverse dis-crimination network that focuses on the signature stroke parts to extract features by reversing the foreground and background of signature images,which effectively solves the problem of little effective *** solve the problem of high intraclass variability of signature images,we add multi-path attention modules between discriminative streams and inverse streams to enhance the discriminative features of signature ***,a multi-path discrimination loss function is proposed,which does not require the feature representation of the samples with the same class label to be infinitely close,as long as the gap between inter-class distance and the intra-class distance is bigger than the set classification threshold,which radically resolves the problem of high intra-class difference of signature *** addition,this loss can also spur the network to explore the detailed infor-mation on the stroke parts,such as the crossing,thickness,and connection of *** respectively tested on CEDAR,BHSig-Bengali,BHSig-Hindi,and GPDS Synthetic datasets with accuracies of 100%,96.24%,93.86%,and 83.72%,which are more accurate than existing signature verification *** is more helpful to the task of signature authentication in justice and finance.

关键词： Offline signatures biometric verification multi-path discrimination loss attention mechanisms inverse discrimination

来源：评论

学校读者我要写书评

暂无评论

A Triangular Stable Node network based on Self-supervised Learning for personalized prediction

A Triangular Stable Node Network based on Self-supervised Le...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Liu, Qing Gao, Qian Fan, Jun Zhang, Zhiqiang Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Qilu University of Technology Shandong Academy of Sciences Jinan250014 China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology Shandong Academy of Sciences Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan250014 China China Telecom Digital Intelligence Techonology Co Ltd. No.1999 Shunhua road Shandong Jinan250101 China

ISBN: (纸本)9798350368741

In recent years, research has illuminated the potency of implicit data processing in enhancing user preferences. Nevertheless, barriers remain in breaking through the constraints of implicit information. This study aims to bridge this gap by firstly constructing a triangular stable node network model, tailored to manage implicit information with precision. Recognizing the challenge of pinpointing novel structures within large-scale graphs, we propose SLTSNN-a triangular stable node network based on self-supervised learning for personalized prediction. SLTSNN innovates by maximizing mutual information between graph-level and patch-level representations, while augmenting graph representations through extended enhanced representations. Additionally, it incorporates triangular data associations and introduces a triangular allocation attention network, which emphasizes strongly correlated preference features among similar users. Furthermore, SLTSNN employs contrastive learning to maximize mutual information between graph vectors and hidden representations, distinguishing between high-order global and local representations. The model's effectiveness in enhancing user preferences and capturing new graph structures is evidenced by its performance on hit rate and normalized discounted cumulative gain metrics across three datasets. © 2025 IEEE.

关键词： graph contrastive learning graph neural networks recommender systems self-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Research and Innovation in Next Generation Security and Privacy in Industry 5.0 Iot 6

Research and Innovation in Next Generation Security and Priv...

引用

6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Navale, Geeta S. Madala, Ravikiran Managuli, Manjunath Jayalakshmi, N. Kadiravan, G. Rawat, Ruchira Sinhgad Institute of Technology and Science Department of Computer Engineering Maharashtra Pune India Ph.D Information Technology Network and Data Center Engineer University of Cumberlands DurhamNC United States KLS Gogte Institute of Technology Department of Electronics and Communication Engineering Karnataka Belagavi India PSNA College of Engineering and Technology Master of Computer Applications Tamilnadu Dindigul India KL Deemed to Be University Department of Computer Science and Information Technology Andhra Pradsh India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttrakhand Dehradun India

ISBN: (纸本)9798350304480

The objective of the newest manufacturing paradigm, known as 'Industry 5.0,'is to combine human intelligence with cutting-edge technology like the Internet of Things (IoT), artificial intelligence (AI), and robots to develop production systems that are incredibly effective and adaptable. But as we rely more on these technologies, we face additional privacy and security issues that might affect how dependable and trustworthy these systems are. In this report, we examine the most recent advancements in security and privacy for Industry 5.0 IoT and pinpoint the newest trends, obstacles, and possibilities. We also cover how these changes may affect manufacturing in the future and provide advice to scholars, practitioners, and policymakers. © 2023 IEEE.

关键词： artificial intelligence cyber-physical systems human-machine collaboration Industry 5.0 Internet of Things IoT manufacturing privacy robotics security

来源：评论

学校读者我要写书评

暂无评论

Multimedia Fingerprinting Codes Resistant to Linear Attacks and Adversarial Noise

Multimedia Fingerprinting Codes Resistant to Linear Attacks ...

引用

2023 International Symposium on networks, computers and Communications, ISNCC 2023

作者： Fernandez, Marcel Kabatiansky, Grigory Kamel, Ibrahim Miao, Ying Rabie, Tamer Farouk The Technical University of Catalonia Department of Network Engineering Spain Center for Next Generation Wireless and IoT Skolkovo Institute of Science and Technology Russia University of Sharjah Electrical and Computer Engineering United Arab Emirates Institute of Engineering Information and Systems University of Tsukuba Japan

ISBN: (纸本)9798350335590

It has recently been shown that there are no multimedia fingerprinting codes that can find all malicious users when they use arbitrary linear attacks plus adversarial noise. It is shown that such codes exist if the complete recovery property is limited to the IPP property, i.e., the property to find at least one malicious user. Moreover, we extend this property to a property that allows us to detect all users whose contribution to the forgery is large enough. Efficient decoding (tracing traitors) algorithms are developed for these codes. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimization of Data Encryption Algorithms in Information Construction

Optimization of Data Encryption Algorithms in Information Co...

引用

2024 International Conference on Distributed Systems, computer networks and Cybersecurity, ICDSCNC 2024

作者： Zhu, Shuai You, Yi Zhou, Bo Chen, Chuanting Yi, Xueqin Hankou University Network Information Center Wuhan China Hankou University School of Computer Science and Technology Wuhan China Wuhan University of Engineering Science Library and Information Center Wuhan China Hankou University School of Music Wuhan China Hankou University Board Office Wuhan China

ISBN: (纸本)9798350375442

Data encryption algorithms play a crucial role in information construction, effectively protecting data security. The problems in traditional research include a lack of targeting, a balance between efficiency and safety, and a lack of comprehensive consideration. Therefore, this article proposed targeted optimization strategies and methods by in-depth analyzing the needs and scenarios of information construction, combined with the characteristics and problems of data encryption algorithms. Meanwhile, this article also comprehensively considered the integration, deployment, management, and maintenance of algorithms to achieve optimal matching and collaborative work between algorithms and information systems. Through research, this article aimed to promote the application and development of data encryption algorithms in information construction, and improve the efficiency, security, and availability of data encryption algorithms in protecting data security. The results showed that the efficiency of the data encryption algorithm based on RSA (Rivest-Shamir-Adleman) reached the highest of 89.6%. This article provides strong support for the application and development of data encryption algorithms, promoting the sustainable development of information construction and the protection of data security. © 2024 IEEE.

关键词： advanced encryption standard data encryption algorithm information technology construction RSA algorithm

来源：评论

学校读者我要写书评

暂无评论

AoI-based Joint User Scheduling and Transmit Power Optimization in High-speed Railway Mobile networks 13

AoI-based Joint User Scheduling and Transmit Power Optimizat...

引用

13th International Conference on Computing Communication and networking Technologies, ICCCNT 2022

作者： Zhang, Xiang Luan, Ning Lu, Yuping Zhang, Zhifei Dong, Rui Xiong, Ke Engineering Research Center of Network Management Technology for High Speed Railway Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing10044 China

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

This paper investigates the age of information (AoI)-based joint user scheduling and transmit power optimization on high-speed railway mobile networks, where a base station (BS) positioned close to the railway schedules track monitoring sensors and train passengers with a time division multiple access (TDMA) manner to fulfill the uplink transmissions. In order to minimize the average achievable AoI of the sensors, we formulate an optimization problem subject to the constraints of the minimal amount of data required to be uploaded by passengers and the available transmit power of the users including both the sensors and the passengers, by optimizing the user scheduling and transmit power. To efficiently solve the problem in the fast varying high-mobility environment, an algorithm based on deep Q-networks (DQN) is proposed, where the weighted sum of the sensors' AoI and the passengers' remaining amount of data to transmit are integrated into the reward function. Simulation results show that the proposed DQN-based algorithm reduces the average AoI of the sensors greatly, about 70% and 60% compared with traditional random algorithm and round-robin algorithm, respectively. Moreover, the increment of the numbers of passengers deteriorates the AoI performance, but among all simulated algorithms, the AoI achieved by our presented DQNbased algorithm is least affected by the numbers of passengers. © 2022 IEEE.

关键词： Wireless networks

来源：评论

学校读者我要写书评

暂无评论

Handover Enhancement in High-Speed Railway 5G networks: A LSTM-based Prediction Method 13

Handover Enhancement in High-Speed Railway 5G Networks: A LS...

引用

13th International Conference on Computing Communication and networking Technologies, ICCCNT 2022

作者： Lu, Yuping Zhang, Cuntao Chen, Deen Zhang, Wanle Xiong, Ke Engineering Research Center of Network Management Technology for High Speed Railway Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing10044 China

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

This paper focuses on the handover performance enhancement of high-speed railway (HSR) 5G millimeter wave(mmWave) networks. As starting the handover at different time may yield very different performances, we propose a Long Short Term Memory (LSTM)-based prediction method to find a proper handover point in advance to alleviate the high handover delay and link interruption-prone problems of traditional A3 handover method. By learning the historical trend of Reference Signal Receiving Power (RSRP) and predicting the future changes of RSRP based on the LSTM encoder-decoder network, the proposed LSTM-based prediction method is able to enhance the handover performance of HSR 5G networks. Simulation results show that compared with traditional A3 method, our proposed LSTM-based prediction method reduces the probability of link interruption, improve the stability of the quality of service (QoS) during the handover process. © 2022 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：