检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

6,728 篇 会议
40 篇 期刊文献
34 册 图书

馆藏范围

6,802 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,043 篇 工学
- 3,663 篇 计算机科学与技术...
- 3,147 篇 软件工程
- 1,333 篇 信息与通信工程
- 722 篇 控制科学与工程
- 646 篇 生物工程
- 546 篇 电气工程
- 354 篇 安全科学与工程
- 293 篇 电子科学与技术（可...
- 282 篇 网络空间安全
- 258 篇 动力工程及工程热...
- 236 篇 生物医学工程（可授...
- 234 篇 交通运输工程
- 211 篇 机械工程
- 172 篇 光学工程
- 128 篇 化学工程与技术
- 120 篇 仪器科学与技术
1,698 篇 理学
- 845 篇 数学
- 683 篇 生物学
- 280 篇 物理学
- 256 篇 统计学（可授理学、...
- 178 篇 化学
- 142 篇 系统科学
985 篇 管理学
- 571 篇 管理科学与工程(可...
- 503 篇 图书情报与档案管...
- 291 篇 工商管理
386 篇 法学
- 225 篇 社会学
- 177 篇 法学
217 篇 医学
- 165 篇 临床医学
- 163 篇 基础医学(可授医学...
137 篇 经济学
- 132 篇 应用经济学
82 篇 教育学
56 篇 农学
22 篇 军事学
18 篇 文学

主题

352 篇 network security
210 篇 security
195 篇 deep learning
169 篇 internet of thin...
135 篇 machine learning
130 篇 blockchain
129 篇 software
98 篇 intrusion detect...
90 篇 feature extracti...
80 篇 neural networks
72 篇 cybersecurity
71 篇 convolutional ne...
66 篇 software defined...
66 篇 cryptography
64 篇 privacy
62 篇 computational mo...
61 篇 training
60 篇 convolution
56 篇 authentication
56 篇 cloud computing

机构

78 篇 school of cyber ...
75 篇 institute of inf...
51 篇 college of compu...
41 篇 chitkara univers...
37 篇 school of comput...
36 篇 chinese academy ...
31 篇 school of inform...
28 篇 university of ch...
26 篇 shandong provinc...
25 篇 school of cyber ...
24 篇 shenzhen univers...
22 篇 school of comput...
20 篇 purple mountain ...
19 篇 school of comput...
19 篇 university of ch...
19 篇 school of softwa...
19 篇 school of softwa...
18 篇 peng cheng labor...
17 篇 college of compu...
17 篇 school of comput...

作者

15 篇 sharma ishu
12 篇 liu yang
11 篇 li bo
10 篇 zhang lei
10 篇 zhang bo
9 篇 iqbal muhammad w...
9 篇 chen chen
9 篇 yang wei
9 篇 tiwari mohit
8 篇 zhang yuqing
8 篇 yang yang
8 篇 ishu sharma
8 篇 liu chang
8 篇 liu qingyun
8 篇 li hui
7 篇 wang jing
7 篇 xu yuwei
7 篇 mohit tiwari
7 篇 wang xu
7 篇 qingyun liu

语言

6,526 篇 英文
268 篇 其他
57 篇 中文
2 篇 土耳其文
1 篇 德文
1 篇 葡萄牙文

检索条件"任意字段=2023 International Conference on Computer Network Security and Software Engineering, CNSSE 2023"

共 6802 条记录，以下是201-210 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Bi-directional LSTM-Attention Chinese Text Classification Model Based on Subsampling Optimization

Bi-directional LSTM-Attention Chinese Text Classification Mo...

引用

2023 international conference on Cyber security, Artificial Intelligence, and Digital Economy, CSAIDE 2023

作者： Lv, Jingze Huang, Wuzhe School of Software Computer and Information Science Southwest University Chongqing400715 China

ISBN: (纸本)9781510666597

This paper proposes a text classification model based on a bi-directional LSTM network with attention mechanism and subsampling in the word vector stage. Firstly, we use the Skip-gram model in Word2Vec for feature extraction, and then combine the two-way LSTM network with subsampling to extract and classify the key semantic information in the text, and integrate the Attention mechanism to optimize the generation weights, enhance the feature transfer between layers, and focus attention on the high weight words. Experimental results on different categories of open datasets show that the proposed model improves the recognition and extraction of high-featured content compared to a single network, and can effectively improve classification accuracy. © 2023 SPIE.

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

A Smart NIDS Design for SDN-based Cloud IoT network using Optimal Path Selection and RNN 9

A Smart NIDS Design for SDN-based Cloud IoT Network using Op...

引用

9th international conference on Signal Processing and Communication, ICSC 2023

作者： Kumar, Narendra Aeron, Anurag Dawar, Ishaan Kumar, Santosh Department of Computer Science and Engineering Amity University Jharkhand Ranchi India School of Computing DIT University Dehradun Dehradun India Computer science and Information Technology Siksha 'O' Anusandhan University Bhubaneshwar India

ISBN: (纸本)9798350383201

The Internet of Things (IoT) has greatly increased the possibility for developing intelligent connections and applications in many facets of daily life. Traditional security solutions frequently fail to solve security issues in cloud-based IoT systems, proving ineffective and insufficient. software Defined networking (SDN), which effectively detects and monitors network security vulnerabilities thanks to its programmable characteristics, presents a viable solution to these problems. In order to strengthen computer systems and fend off threats to network security, machine learning (ML) techniques have recently been included into SDN-network Intrusion Detection Systems (NIDS). Deep learning (DL), one of these cutting-edge ML techniques, has become more popular in the SDN environment. For SDN-based cloud IoT networks, this paper design an efficient path selection system in this study utilizing DL approaches. The strategy comprises employing a Recurrent Neural network (RNN) to identify threats and a selection mechanism to pick the best route for data delivery. This study performed tests on two datasets, KDD and UNSWNB15, and the results show that the suggested RNN outperformed existing DL methods by achieving an amazing accuracy ranging from 91% to 95% on both datasets. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Adapting Graph Structure for IoT network: A Performance Analysis 21

Adapting Graph Structure for IoT Network: A Performance Anal...

引用

21st international Joint conference on computer Science and software engineering (JCSSE)

作者： Sejan, Mohammad Abrar Shakil Rahman, Md Habibur Aziz, Md Abdul Song, Hyoung-Kyu Tabassum, Rana Sejong Univ Dept Informat & Commun Engn Seoul South Korea Sejong Univ Dept Convergence Engn Intelligent Drone Seoul South Korea

ISBN: (纸本)9798350381771;9798350381764

Graph structures can effectively replicate intricate relationships among diverse entities, offering valuable insights into the interconnections among nodes. In this paper, we leverage graph neural network (GNN) algorithms for the classification of Internet of Things (IoT) nodes based on their connectivity and features. The node classification task involves transforming the IoT network into a graph structure, encompassing both fully connected and randomly connected graphs. In fully connected graph each node is connected to other nodes and randomly connected graphs have missing connections. Furthermore, two GNN methodologies, namely ARMAConv and Cluster-GCN, are employed for precise classification. The simulation results reveal that Cluster-GCN outperforms ARMAConv, achieving a higher success rate in node classification.

关键词： Graph data structure Graph neural network Machine learning Internet of things

来源：评论

学校读者我要写书评

暂无评论

An analysis of network security Attacks and their mitigation for Cognitive Radio Communication 9

An analysis of Network Security Attacks and their mitigation...

引用

9th international conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Gayathri, N. Anandakumar, H. Gowri, S. Keerthika, J. Nithyapriya, S. Sri Eshwar College of Engineering Computer Science and Engineering Tamilnadu Coimbatore India Sri Eshwar College of Engineering Department of Artificial Intelligence and Data Science Tamilnadu Coimbatore India

ISBN: (纸本)9798350397376

The primary motivator after the evolution of cognitive radio is the lack of utilization of the spectrum. This technology adds new functionality in the physical layer, data link sub-layer, Transmission Control Protocol/Internet Protocol layer, and Transport layers of the hierarchy of software layers. The majority of the currently available research in cognitive radio has concentrated on security challenges at the physical, MAC layers. Over the past two decades, cyber security threats and problems have grown significantly, especially in cognitive radio networks. This study describes and analyzes various attacks that target each layer at its protocol stack. Each attack's specific detection techniques and defenses are also examined and contrasted. © 2023 IEEE.

关键词： Cognitive radio

来源：评论

学校读者我要写书评

暂无评论

Are We Aware? An Empirical Study on the Privacy and security Awareness of Smartphone Sensors 21

Are We Aware? An Empirical Study on the Privacy and Security...

引用

21st IEEE/ACIS international conference on software engineering Research, Management and Applications, SERA 2023

作者： Champa, Arifa I. Rabbi, Md Fazle Eishita, Farjana Z. Zibran, Minhaz F. Idaho State University Department of Computer Science United States

ISBN: (纸本)9798350345889

Smartphones are equipped with a wide variety of sensors, which can pose significant security and privacy risks if not properly protected. To assess the privacy and security risks of smartphone sensors, we first systematically reviewed 55 research papers. Driven by the findings of the systematic review, we carried out a follow-up questionnaire-based survey on 23 human end-users. The results reflect that the participants have a varying level of familiarity with smartphone sensors, and there is a noticeable dearth of awareness about the potential threats and preventive measures associated with these sensors. The findings from this study will inform the development of effective solutions for addressing security and privacy in mobile devices and beyond. © 2023 IEEE.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

IoT security: A Deep Learning-Based Approach for Intrusion Detection and Prevention

IoT Security: A Deep Learning-Based Approach for Intrusion D...

引用

2023 international conference on Evolutionary Algorithms and Soft Computing Techniques, EASCT 2023

作者： Kauhsik, Bhanu Nandanwar, Himanshu Katarya, Rahul Delhi Technological University Dept. of Software Engineering Delhi India Delhi Technological University Dept. of Computer Science and Engineering Delhi India

ISBN: (纸本)9798350313413

The size and market worth of the Internet of Things (IoT) have expanded, but unfortunately, the likelihood of user data being compromised has also risen. This presents a notable danger that has the potential to create disorder. Consequently, the main aim of this paper is to recognize any weaknesses within existing security solutions and suggest an innovative approach to address them. In order to accomplish this, the paper puts forth four research inquiries concerning IoT security that leverage Machine Learning and Deep Learning techniques. Additionally, it conducts an extensive review of the latest publications and concludes that a combination of specific techniques can provide a potential solution to the security problems in IoT. Overall, the findings of this study suggest that this systematic literature review could help in significantly enhancing the security of IoT devices and applications, safeguarding user data from unauthorized access and potential misuse. © 2023 IEEE.

关键词： Cyberattack Deep Learning Internet of Things (IOT) Intrusion Detection System (IDS) network security

来源：评论

学校读者我要写书评

暂无评论

引用

15th international conference on Communication Systems and networks (COMSNETS)

作者： Bopche, Ghanshyam S. Tiwari, Deepnarayan Rai, Gopal N. Natl Inst Technol Dept Comp Applicat Tiruchirappalli India NPCI Mumbai Maharashtra India Collins Aerosp India Pvt Ltd Hyderabad Telangana India

ISBN: (纸本)9781665477062

The network security assessment is vital for improving the overall security posture. With diverse opportunities for using networking devices and configuring them, varying software application portfolios, and the increased flexibility of using numerous applications, today's computer networks are subject to continuous evolution. Such ever-growing computer networks in size and complexity lead to information exposure to an increased threat landscape and attack surface variation. The network attack surface constitutes exploitable technical vulnerabilities, software/hardware misconfigurations (i.e., configuration gaps), vulnerable service connectivities, and service-cum-user privileges. An adversary may exploit the network attack surface to penetrate the enterprise networks incrementally. The discovery of new vulnerabilities and vague access control rules can further set off the attack surface variation. Hence, it is essential to consider the temporal aspect of network security. Attack graph, a graphical network security modeling tool, succinctly captures the attack surface of a vulnerable network in the form of initial security conditions, much needed for an adversary for successful incremental network penetration. Existing attack graph-based metrics are inadequate in capturing the variation in the attack surface. We propose to use a Boolean similarity metric to assess the similarity between the goal-oriented attack graphs generated successively for an enterprise network within the chosen sampling interval. We represent individual attack graphs as a Boolean expression to serve our purpose. A Boolean expression is a sum-of-product expression, i.e., a disjunction of attack paths, each a conjunction of initial conditions. We have conducted a set of experiments to validate the efficacy and applicability of the Boolean similarity metric. The results indicate that the Boolean similarity measure can detect the variation in the network attack surface.

关键词： Attack Surface Attack Graph security Metric security Performance Monitoring Boolean Similarity Measure

来源：评论

学校读者我要写书评

暂无评论

Intelligent security Aware Routing: Using Model-Free Reinforcement Learning 32

Intelligent Security Aware Routing: Using Model-Free Reinfor...

引用

32nd international conference on computer Communications and networks, ICCCN 2023

作者： Mudgerikar, Anand Bertino, Elisa Purdue University Department of Computer Science United States

ISBN: (纸本)9798350336184

With the emergence and successful deployment of software defined networks (SDN), zero-trust security architecture, and network function virtualization (NFV) in large scale modern enterprise and 5G networks, it is possible to build 'smart' network controllers that leverage machine learning (ML) to learn policies for optimal and secure traffic engineering. Deep Reinforcement Learning (DRL) is an effective technique for building such smart controllers because of its model-free nature and ability to learn policies dynamically through experience without requiring extensive training data. However, conventional DRL frameworks are geared to maximize functionality and do not take network security into account. To address such a gap, we propose a security-aware DRL framework, STE-SDN that learns 'intelligent policies' for traffic engineering (routing) to both maximize functionality gain and minimize security risk. We instantiate our framework in a simulated SDN environment of 5000 nodes with different security services and three attack classes: DDoS, Web-based and Brute-Force attacks. We then analyze our framework using the CICIDS-17 dataset in terms of performance and effectiveness in mitigating security risks. We find that our RL framework reduces detection loss by 85.8% and maintains close to optimal performance for 78.8%. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Predicting and Evaluating Anomaly Detection and Traffic Analysis on software Defined networks Using a Hybrid Machine Learning Approach 5th

Predicting and Evaluating Anomaly Detection and Traffic Anal...

引用

5th international conference on Computing and network Communications, CoCoNet 2023

作者： Darshan, S. Radhika, N. Radhika, G. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9789819745395

In the rapidly evolving landscape of software Defined networks (SDNs), network security is of paramount importance. This research paper presents a comprehensive study on anomaly detection and traffic analysis in SDNs using machine learning algorithms. The study addresses a critical research gap by proposing an effective methodology for detecting network anomalies and analyzing traffic patterns. Leveraging a carefully selected dataset, we evaluate the performance of Logistic Regression, Decision Tree, Random Forest, Neural networks and Hybrid Models. The results demonstrate the superior performance of the hybrid model built using Decision Tree and Neural networks and the competitive accuracy of Neural networks in SDN anomaly detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

A security Survey of NFV: From Causes to Practices 3

A Security Survey of NFV: From Causes to Practices

引用

3rd international conference on Consumer Electronics and computer engineering, ICCECE 2023

作者： He, Gang Liao, Xingxing Liu, Caixia School of Cyber Science and Engineering Southeast University Nanjing211189 China Purple Mountain Laboratories Nanjing211100 China National Digital Switching System Engineering and Technological R and D Center Zhengzhou450002 China Academy of Military Sciences Institute of System Engineering Beijing100091 China

ISBN: (纸本)9798350331578

network Function Virtualization (NFV) is proposed as new technology to address massive proprietary devices, high operation costs, poor flexibility and other problems in current traditional network. By separating network functions and proprietary devices, NFV can significantly reduce operation costs and enable flexible configuration of services, etc. Now NFV is widely used in various fields. However, due to virtualization and softwareization and other technical characteristics, NFV faces more serious security threats compared to traditional networks. This paper focuses on analyzing the NFV security threats under the new technology and summarizes them according to the causes of security threats. Subsequently, based on the results of the analysis, we propose the corresponding safety practice solutions. Finally, we prospect the research directions for improving NFV security. © 2023 IEEE.

关键词： network function virtualization

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 17 18 19 20 21 22 23 24 25 26 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：