检索结果-内蒙古大学图书馆

Application of meta-learning in cyberspace security:a survey

Digital Communications and Networks 2023年第1期9卷 67-78页

作者： Aimin Yang Chaomeng Lu Jie Li Xiangdong Huang Tianhao Ji Xichang Li Yichao Sheng Hebei Key Laboratory of Data Science and Application North China University of Science and TechnologyTangshan063000China Hebei Engineering Research Center for the Intelligentization of Iron Ore Optimization and Ironmaking Raw Materials Preparation Processes North China University of Science and TechnologyTangshan063000China The Key Laboratory of Engineering Computing in Tangshan City North China University of Science and TechnologyTangshan063000China

In recent years,machine learning has made great progress in intrusion detection,network protection,anomaly detection,and other issues in ***,these traditional machine learning algorithms usually require a lot of data to learn and have a low recognition rate for unknown *** them,“one-shot learning”,“few-shot learning”,and“zero-shot learning”are challenges that cannot be ignored for traditional machine *** more intractable problem in cyberspace security is the changeable attack *** a new attack mode appears,there are few or even zero samples that can be ***-learning comes from imitating human problem-solving methods as humans can quickly learn unknown things based on their existing knowledge when *** purpose is to quickly obtain a model with high accuracy and strong generalization through less data *** article first divides the meta-learning model into five research directions based on different principles of *** are model-based,metric-based,optimization-based,online-learning-based,or stacked ***,the current problems in the field of cyberspace security are categorized into three branches:cyber security,information security,and artificial intelligence security according to different ***,the application research results of various meta-learning models on these three branches are *** the same time,based on the characteristics of strong generalization,evolution,and scalability of meta-learning,we contrast and summarize its advantages in solving ***,the prospect of future deep application of meta-learning in the field of cyberspace security is summarized.

关键词： Meta-learning Cyberspace security Machine learning Few-shot learning

来源：评论

学校读者我要写书评

暂无评论

Set pair three-way overlapping community discovery algorithm for weighted social internet of things

引用

Digital Communications and Networks 2023年第1期9卷 3-13页

作者： Chunying Zhang Jing Ren Lu Liu Shouyue Liu Xiaoqi Li Liya Wang College of Science North China University of Science and TechnologyTangshanHebeiChina Hebei Engineering Research Center for the Intelligentization of Iron Ore Optimization and Ironmaking Raw Materials Preparation Processes North China University of Science and TechnologyTangshanHebeiChina Hebei Key Laboratory of Data Science and Application North China University of Science and TechnologyTangshanHebeiChina The Key Laboratory of Engineering Computing in Tangshan City North China University of Science and TechnologyTangshanHebeiChina Tangshan Intelligent Industry and Image Processing Technology Innovation Center North China University of Science and TechnologyTangshanHebeiChina

There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping *** idea of set pair information grain computing and clustering is introduced to solve the above problems so as to accurately describe the similarity between nodes and fully explore the multi-community structure.A Set Pair Three-Way Overlapping Community Discovery Algorithm for Weighted Social Internet of Things(WSIoT-SPTOCD)is *** the local network structure,which fully considers the topological information between nodes,the set pair connection degree is used to analyze the identity,difference and reverse of neighbor *** similarity degree of different neighbor nodes is defined from network edge weight and node degree,and the similarity measurement method of set pair between nodes based on the local information structure is *** to the number of nodes'neighbors and the connection degree of adjacent edges,the clustering intensity of nodes is defined,and an improved algorithm for initial value selection of k-means is *** nodes are allocated according to the set pair similarity between nodes and different ***-way community structures composed of a positive domain,boundary domain and negative domain are generated ***,the overlapping node set is generated according to the calculation results of community node ***,experiments are carried out on artificial networks and real *** results show that WSIoT-SPTOCD performs well in terms of standardized mutual information,overlapping community modularity and F1.

关键词： Social internet of things Set pair analysis K-means Local information structure Overlapping community

来源：评论

学校读者我要写书评

暂无评论

Review on application progress of federated learning model and security hazard protection

引用

Digital Communications and Networks 2023年第1期9卷 146-158页

作者： Aimin Yang Zezhong Ma Chunying Zhang Yang Han Zhibin Hu Wei Zhang Xiangdong Huang Yafeng Wu Hebei Engineering Research Center for the Intelligentization of Iron Ore Optimization and Ironmaking Raw Materials Preparation Processes North China University of Science and TechnologyTangshanHebeiChina Hebei Key Laboratory of Data Science and Application North China University of Science and TechnologyTangshanHebeiChina The Key Laboratory of Engineering Computing in Tangshan City North China University of Science and TechnologyTangshanHebeiChina Tangshan Intelligent Industry and Image Processing Technology Innovation Center North China University of Science and TechnologyTangshanHebeiChina College of Science North China University of Science and TechnologyTangshanHebeiChina College of Artificial Intelligence North China University of Science and TechnologyTangshanHebeiChina

Federated learning is a new type of distributed learning framework that allows multiple participants to share training results without revealing their data *** data privacy becomes more important,it becomes difficult to collect data from multiple data owners to make machine learning predictions due to the lack of data *** is forced to be stored independently between companies,creating“data silos”.With the goal of safeguarding data privacy and security,the federated learning framework greatly expands the amount of training data,effectively improving the shortcomings of traditional machine learning and deep learning,and bringing AI algorithms closer to our *** the context of the current international data security issues,federated learning is developing rapidly and has gradually moved from the theoretical to the applied *** paper first introduces the federated learning framework,analyzes its advantages,reviews the results of federated learning applications in industries such as communication and healthcare,then analyzes the pitfalls of federated learning and discusses the security issues that should be considered in applications,and finally looks into the future of federated learning and the application layer.

关键词： data silos Machine learning Federated learning Privacy protection Learning framework

来源：评论

学校读者我要写书评

暂无评论

Non-rigid registration of medical images based on S^(1/2)(Δ_(mn)^((2)))non-tensor product Bspline

引用

Visual Computing for Industry,Biomedicine,and Art 2022年第1期5卷 57-70页

作者： Qi Zheng Chaoyue Liu Jincai Chang College of Sciences North China University of Science and TechnologyTangshan 063210China Hebei Key Laboratory of Data Science and Application North China University of Science and TechnologyTangshan 063210China

In this study,a non-tensor product B-spline algorithm is applied to the search space of the registration process,and a new method of image non-rigid registration is *** tensor product B-spline is a function defined in the two directions of x and y,while the non-tensor product B-spline S^(1/2)(Δ_(mn)^((2)))is defined in four directions on the 2-type *** certain problems,using non-tensor product B-splines to describe the non-rigid deformation of an image can more accurately extract the four-directional information of the image,thereby describing the global or local non-rigid deformation of the image in more ***,it provides a method to solve the problem of image deformation in multiple *** addition,the region of interest of medical images is irregular,and usually no value exists on the boundary *** value of the basis function of the non-tensor product B-spline on the boundary triangle is only *** algorithm process is *** algorithm performs completely automatic non-rigid registration of computed tomography and magnetic resonance imaging images of *** particular,this study compares the performance of the proposed algorithm with the tensor product B-spline registration *** results elucidate that the proposed algorithm clearly improves the accuracy.

关键词： Non-rigid registration Diagonal direction Non-tensor product type B-spline Boundary triangle domain

来源：评论

学校读者我要写书评

暂无评论

Research on Nilpotent Groups Based on Fuzzy Hypergroups

引用

Journal of Applied Mathematics and Physics 2025年第1期13卷 148-156页

作者： Yi Yan Yan Yan Xinru Shang College of Science North China University of Science and Technology Tangshan China Hebei Key Laboratory of Data Science and Application Tangshan China

In this paper, by constructing the smallest equivalence relation θ∗on a finite fuzzy hypergroup H, the quotient group (the set of equivalence classes) H/θ∗is a nilpotent group, and the nilpotent group is characterized by the strong fuzzy regularity of the equivalence relation. Finally, the concept of θ-part of fuzzy hypergroup is introduced to determine the necessary and sufficient condition for the equivalence relation θto be transitive.

关键词： Fuzzy Hypergroup Equivalence Relation Strong Fuzzy Regular Relation Nilpotent Group

来源：评论

学校读者我要写书评

暂无评论

Gaussian Distance Weighted Algorithm for Geometric Characteristics of Three-Dimensional Discrete Curves

引用

Journal of Applied Mathematics and Physics 2024年第10期12卷 3599-3612页

作者： Liyan Zhang Haiyi Ai Shaohong Yan Haili Chen Jiali Zou Junqing Zhang College of Science North China University of Science and Technology Tangshan China Hebei Provincial Key Laboratory of Data Science and Applications North China University of Science and Technology Tangshan China Key Laboratory of Data Science in Tangshan Tangshan China Tangshan Zhongyu Technology Development Co. Ltd. Tangshan China

Discrete curves are composed of a set of ordered discrete points distributed at the intersection of the scanning plane and the surface of the object. In order to accurately calculate the geometric characteristics of any point on the discrete curve, a distance-based Gaussian weighted algorithm is proposed to estimate the geometric characteristics of three-dimensional space discrete curves. According to the definition of discrete derivatives, the algorithm fully considers the relative position difference between a specific point and its neighboring points, introduces the distance weighting idea, and integrates the smoothing strategy. The experiment uses two spatial discrete curves for uniform and non-uniform sampling, and compares them with two commonly used estimation algorithms. The comparative analysis is carried out in terms of sampling density, neighborhood radius and noise resistance. The experimental results show that the Gaussian distance weighted algorithm is effective and provides an efficient algorithm for underground pipeline safety detection.

关键词： Discrete Curve Angle Weight Algorithm Comparison Underground Pipeline Inspection

来源：评论

学校读者我要写书评

暂无评论

Research on θ -Intuitionistic Fuzzy Homomorphism Theory

引用

Journal of Applied Mathematics and Physics 2024年第10期12卷 3579-3589页

作者： Yue Wang Yan Yan Xinru Shang College of Science North China University of Science and Technology Tangshan China Hebei Key Laboratory of Data Science and Application Tangshan China

Fuzzy homomorphism is an important research content of fuzzy group theory, different fuzzy mappings will produce different fuzzy homomorphisms. In this paper, the fuzzy homomorphism of groups is generalized. Firstly, the θ-intuitionistic fuzzy mapping is defined, and the θ-intuitionistic fuzzy homomorphism of groups is obtained. The properties of intuitionistic fuzzy subgroups and intuitionistic fuzzy normal subgroups are studied under the θ-intuitionistic fuzzy homomorphism of groups, and the fundamental theorem of θ-intuitionistic fuzzy homomorphism is proved.

关键词： -Intuitionistic Fuzzy Homomorphism Intuitionistic Fuzzy Subgroup Intuitionistic Fuzzy Normal Subgroup

来源：评论

学校读者我要写书评

暂无评论

Federated Learning Model of Multi key Homomorphic Encryption on the basis of Internet of Things

Automation, Robotics and Communications for Industry 4.0/5.0

引用

Automation, Robotics and Communications for Industry 4.0/5.0 2023年 2023卷 138-144页

作者： Zhai, Ran. Chen, Xuebin Ma, Ruikui Pei, Langtao North China University of Science and Technology HeBei TangShan063210 China Hebei Key Laboratory of Data Science and Application HeBei TangShan063210 China Tangshan Key Laboratory of Data Science HeBei TangShan063210 China

With the rapid development of the Internet of Things, a large number of mobile devices need to process massive data cooperatively. However, the privacy protection of the data at the participating end is crucial during collaborative training. Federated Learning as a Distributed Machine Learning Framework, the data can be kept locally to complete collaborative training. However, during parameter transmission in federated learning, parameter leakage will lead to raw data leakage. Encrypting parameters using homomorphic encryption solves this problem. However, in homomorphic encryption, multiple participants use the same key, so once any participant disclose the public key, the entire model security will be affected. Therefore, multi key homomorphic encryption is applied to the federated learning model. In multi key homomorphic encryption, participants use their own public keys to encrypt the parameters and jointly use the private keys to decrypt. This process avoid the impact on the model security caused by the key disclosure of a single participant. The experimental results show that the security of federated learning model on the basis of multi key homomorphic encryption technology has better security than traditional federated learning models. Meanwhile, the accuracy of training was not affected. © 2023, International Frequency Sensor Association (IFSA). All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

RNaAE: A Novel Approach for Identifying Unseen Railway Anomalies 17

RNaAE: A Novel Approach for Identifying Unseen Railway Anoma...

引用

17th IEEE International Conference on Signal Processing, ICSP 2024

作者： Zhang, Jiayu Guan, Qingji Liu, Junbo Huang, Yaping Guo, Jianyong Beijing Jiaotong University Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing China China Academy of Railway Science Corporation Limited Infrastructure Inspector Center Beijing China Tangshan Research Institute Beijing Jiaotong University Tangshan China National Engineering Research Center for Digital Construction and Evaluation Urban Rail Transit Tianjin China

ISBN: (纸本)9798350387384

Detecting abnormal objects in railway track inspection images using vision-based technology is a crucial task for ensuring the safety of railway transportation. Traditional supervised object detection methods fail to achieve satisfactory results due to the diverse categories of abnormal objects and the lack of abnormal samples. Even though the widely used Autoencoder can leverage reconstruction errors to detect anomalies without using abnormal data, they tend to generate a relatively high number of false positives. In this paper, we address the task in an unsupervised manner and propose a novel Random Network-Assisted Autoencoder, called RNaAE, for identifying unseen abnormal objects. Specifically, we first design a learnable network to fit a randomly initialized stochastic network with fixed weights, where the difference between two predictions can then be used to estimate whether the candidate object is anomalous. After combined with a traditional Autoencoder, a Gaussian mixture model is then used to classify the candidate box into normal and abnormal by anomaly scores. Extensive experiments conducted on our collected railway anomaly dataset demonstrate that the proposed RNaAE exceeds previous stateof-the-art methods, achieving 98.23% and 92.02% in terms of AUROC and F1-score. © 2024 IEEE.

关键词： Railroads

来源：评论

学校读者我要写书评

暂无评论

A review of big data technology and its application in cancer care

引用

Computers in Biology and Medicine 2024年 176卷 108577-108577页

作者： Xiao, Tianyun Kong, Shanshan Zhang, Zichen Hua, Dianbo Liu, Fengchun Hebei Key Laboratory of Data Science and Application North China University of Science and Technology Hebei Tangshan063210 China The Key Laboratory of Engineering Computing in Tangshan City North China University of Science and Technology Hebei Tangshan063210 China College of Science North China University of Science and Technology Hebei Tangshan063210 China Hebei Engineering Research Center for the Intelligentization of Iron Ore Optimization and Ironmaking Raw Materials Preparation Processes North China University of Science and Technology Hebei Tangshan China Tangshan Intelligent Industry and Image Processing Technology Innovation Center North China University of Science and Technology Hebei Tangshan China Beijing Sitairui Cancer Data Analysis Joint Laboratory Beijing101149 China

The development of modern medical devices and information technology has led to a rapid growth in the amount of data available for health protection information, with the concept of medical big data emerging globally, along with significant advances in cancer care relying on data-driven approaches. However, outstanding issues such as fragmented data governance, low-quality data specification, and data lock-in still make sharing challenging. Big data technology provides solutions for managing massive heterogeneous data while combining artificial intelligence (AI) techniques such as machine learning (ML) and deep learning (DL) to better mine the intrinsic connections between data. This paper surveys and organizes recent articles on big data technology and its applications in cancer, dividing them into three different types to outline their primary content and summarize their critical role in assisting cancer care. It then examines the latest research directions in big data technology in cancer and evaluates the current state of development of each type of application. Finally, current challenges and opportunities are discussed, and recommendations are made for the further integration of big data technology into the medical industry in the future. © 2024 Elsevier Ltd

关键词： Big data

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：