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

5,010 篇 会议
280 册 图书
60 篇 期刊文献

馆藏范围

5,350 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,855 篇 工学
- 2,546 篇 计算机科学与技术...
- 1,705 篇 软件工程
- 944 篇 信息与通信工程
- 368 篇 电气工程
- 306 篇 控制科学与工程
- 182 篇 网络空间安全
- 126 篇 动力工程及工程热...
- 125 篇 电子科学与技术（可...
- 119 篇 安全科学与工程
- 111 篇 机械工程
- 102 篇 生物工程
- 70 篇 建筑学
- 69 篇 仪器科学与技术
- 54 篇 生物医学工程（可授...
- 45 篇 土木工程
- 43 篇 交通运输工程
614 篇 理学
- 369 篇 数学
- 118 篇 生物学
- 103 篇 系统科学
- 100 篇 统计学（可授理学、...
- 84 篇 物理学
488 篇 管理学
- 337 篇 管理科学与工程(可...
- 189 篇 图书情报与档案管...
- 162 篇 工商管理
242 篇 法学
- 166 篇 法学
- 82 篇 社会学
78 篇 医学
- 65 篇 临床医学
- 63 篇 基础医学(可授医学...
- 51 篇 公共卫生与预防医...
62 篇 经济学
- 62 篇 应用经济学
41 篇 军事学
17 篇 农学
16 篇 教育学
12 篇 文学
1 篇 艺术学

主题

504 篇 security
346 篇 wireless sensor ...
304 篇 computer network...
253 篇 protocols
247 篇 computer archite...
219 篇 intrusion detect...
213 篇 authentication
210 篇 computer communi...
205 篇 ip networks
193 篇 computer crime
172 篇 servers
165 篇 computer securit...
161 篇 network security
158 篇 information secu...
154 篇 internet of thin...
153 篇 distributed comp...
148 篇 cryptography
146 篇 computer science
145 篇 computational mo...
142 篇 internet

机构

25 篇 shandong provinc...
21 篇 key laboratory o...
13 篇 shandong fundame...
12 篇 chitkara univers...
10 篇 information syst...
10 篇 department of co...
9 篇 shandong enginee...
9 篇 king saud univer...
9 篇 school of comput...
9 篇 institute of inf...
8 篇 school of comput...
8 篇 department of co...
8 篇 department of co...
7 篇 key laboratory o...
7 篇 school of comput...
7 篇 department of la...
7 篇 hannam universit...
6 篇 shandong enginee...
6 篇 chinese acad sci...
6 篇 department of el...

作者

19 篇 eyas el-qawasmeh
11 篇 tai-hoon kim
9 篇 hammoudeh mohamm...
9 篇 dominik ślęzak
9 篇 obaidat mohammad...
9 篇 igor kotenko
8 篇 isaac woungang
8 篇 azizah abd manaf
8 篇 jasni mohamad za...
7 篇 osvaldo gervasi
7 篇 yanmin zhu
7 篇 mohammad s. obai...
7 篇 barolli leonard
7 篇 natrayan l
7 篇 lin zhang
7 篇 wei wang
7 篇 mukaddim pathan
6 篇 klaus wehrle
6 篇 zarai faouzi
6 篇 yunhao liu

语言

4,998 篇 英文
321 篇 其他
43 篇 中文
1 篇 葡萄牙文

检索条件"任意字段=International Conference on Security in Computer Networks and Distributed Systems, SNDS 2012"

共 5350 条记录，以下是921-930 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：

DDoS Attack Intrusion Detection System with CNN and LSTM Hybridization

DDoS Attack Intrusion Detection System with CNN and LSTM Hyb...

引用

Sustainable Computing and Smart systems (ICSCSS), international conference on

作者： V Poornachander Konga Sathish Kumar Sripelli Jagadish Department of Computer science and Applications Government Degree College (Autonomous) Narsampet Warangal Telangana Department of Computer Science & Engineering Chaitanya (Deemed to be) University Hanamkonda Telangana Dept of CS & AI SR University Ananthasagar Telangana

ISBN: (数字)9798350379990

ISBN: (纸本)9798350391558

distributed Denial of service (DDoS) threats are among the most harmful events to network security. DDoS attacks are considered among the most common types of network attacks. When servers get attacked by these attacks., users experience issues when they try to access those servers for assistance. This caused the need for an effective means of identifying DDoS attacks., which is essential. Research has established that deep learning and machine learning are valuable methods for detecting DDoS attacks. The model has been verified employing the NSLKDD dataset. The seven levels of this type of development enable enhanced performance compared to LSTM and standard CNN. Modules for recognizing and handling defects have been included in this system. Convolutional Neural Network (CNN) and Long Short-Term Memory (CNN-LSTM) techniques are implemented in the anomaly detection model to recognize irregular patterns in traffic effectively. The proposed model utilizes flow rule directions from the controller to detect irregular traffic. It employs IP tracing to connect back to the attacker.

关键词： Training Accuracy Denial-of-service attack Prediction algorithms User experience Convolutional neural networks Servers

来源：评论

学校读者我要写书评

暂无评论

Advancements in Suspicious and Violent Activity Recognition for Intelligent Video Surveillance 3

Advancements in Suspicious and Violent Activity Recognition ...

引用

3rd international conference on Disruptive Technologies, ICDT 2025

作者： Rana, Niyati Parashar, Deepak Bahadure, Nilesh Jethani, Hetal Banerjee, Sudipta Sharma, Kanhaiya Gsfc University Department of Computer Scinece & Engineering Gujarat Vadodara India Symbiosis Institute of Technology Pune Symbiosis International Univesity Dept. of Cse Maharashtra Pune India

ISBN: (纸本)9798331519582

Recognition of suspicious or violent activity in video surveillance has become increasingly important in terms of public safety and security. This synthesis examined state-of-the-art methodologies for detecting anomalous human behaviors-such as machine learning, deep learning, and hybrid approaches. By analyzing key contributions across recent studies, we identify advancements in feature extraction, model architectures such as CNNs, LSTMs, and Conv3D, and their applications to datasets like UCF101 and custom video repositories. The comparative analysis shows promising aspects in terms of performance and reliability, with some techniques such as Time-distributed CNN getting accuracy improvements of over 90%. The issues of practical applications in a real-world scenario, problems with dealing with advanced datasets, and future research directions such as real-time implementation and ethical considerations were discussed. The present study provides an inclusive overview of the current trends in intelligent surveillance systems and the roadmap for innovations in the near future. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

A new ontological approach for multilingual scientific research 23

A new ontological approach for multilingual scientific resea...

引用

Proceedings of the 7th international conference on Future networks and distributed systems

作者： Mohammed Charaf Eddine Meftah Okba Kazar LIAP Laboratory University of El Oued Algeria Smart Computer Science Laboratory (LINFI) Computer Science Department University of Biskra Algeria and Department of Information Systems and Security College of Information Technology United Arab Emirate University United Arab Emirates

ISBN: (纸本)9798400709036

Abstract— Scientific research is all the actions undertaken to produce and develop scientific knowledge. The representation of this knowledge can take various forms: it can be publications, reports, patents, etc. This knowledge can be incorporated into scientific social networks and applications. The scientific social networks in their current form depend on the title, the keywords, and the ontology to compare and link the relationship between different scientific research; there may be different scientific research with the same keywords; the same scientific research may have different titles. In addition, scientific research may be written in different languages, but current scientific social networks do not take into account the multiple languages of researchers and research. they cannot link the relationship and compare scientific research written in different languages. To solve these problems, this paper proposes the use of a multi-lingual ontology to determine and describe scientific research. This work uses ontology in the context of a conceptual indexation, by separating the concept from the term, thus, the result of this work according to the proposed approach will make it possible to express the concept (knowledge extra-linguistic), in different languages, this will allow comparing and linking the relationship between scientific research written in different languages and measuring the percentage of similarity and difference between them. Dealing with multilingualism in scientific research is a very important contribution to this field.

关键词：

来源：评论

学校读者我要写书评

暂无评论

SHAKTI: Securing Hardware IPs by Cascade Gated Multiplexer-Based Logic Obfuscation

SHAKTI: Securing Hardware IPs by Cascade Gated Multiplexer-B...

引用

international conference on VLSI Design

作者： Jugal Gandhi Nikhil Handa Abhay Nayak Diksha Shekhawat M. Santosh Jaya Dofe Jai Gopal Pandey CSIR- Central Electronics Engineering Research Institute (CEERI) Pilani India Academy of Scientific and Innovative Research (AcSIR) Ghaziabad India Birla Institute of Technology and Science (BITS) Pilani India Department of Electrical and Computer Engineering California State University Fullerton CA USA

ISBN: (数字)9798331522445

ISBN: (纸本)9798331522452

The modern distributed chip design chain is increasingly vulnerable to piracy and overproduction. Logic locking has emerged as a prominent solution, allowing chip designers to enhance the security of their hardware intellectual property (IP) by obscuring the functional behavior of the design. Multiplexer (MUX)-based locking is notable for its effectiveness and efficiency. Recent studies have identified its susceptibility to Boolean satisfiability (SAT) and structural learning-based attacks. This article addresses security vulnerabilities and introduces a secure hardware IP design technique with key-controlled cascade gated MUX-based locking (SHAKTI) and its variant SHAKTI + . The proposed techniques integrate a daisy-chained structure and MUXes to improve attack resilience while optimizing resource overhead. The experimental results on ISCAS'85 and ITC'99 benchmark netlists with 64-bit and 128-bit key sizes demonstrate the average area/power/delay overheads for SHAKTI and SHAKTI + are 19.32/16.35/11.86% and 19.45/17.60/11.56%, respectively. security evaluations against the SAT attack demonstrated timeouts for all netlists, obstructing key recovery. The average key prediction accuracy for the SCOPE attack on SHAKTI and SHAKTI + locked designs is only 20.90%. To extend the evaluation, power trace analysis of the locked netlist shows a key-aliasing effect across most locked netlists. The proposed techniques achieve a balanced overhead-security trade-off, strengthening locking against oracle-guided and oracle-less adversarial models.

关键词： Multiplexing Runtime Intellectual property Logic gates Very large scale integration Hardware security Logic IP networks Resilience

来源：评论

学校读者我要写书评

暂无评论

Sequential Pattern Mining: A Proposed Approach for Intrusion Detection systems 23

Sequential Pattern Mining: A Proposed Approach for Intrusion...

引用

Proceedings of the 7th international conference on Future networks and distributed systems

作者： Moemedi Lefoane Ibrahim Ghafir Sohag Kabir Irfan Ullah Awan Computer Science University of Bradford United Kingdom

ISBN: (纸本)9798400709036

Technological advancements have played a pivotal role in the rapid proliferation of the fourth industrial revolution (4IR) through the deployment of Internet of Things (IoT) devices in large numbers. COVID-19 caused serious disruptions across many industries with lockdowns and travel restrictions imposed across the globe. As a result, conducting business as usual became increasingly untenable, necessitating the adoption of new approaches in the workplace. For instance, virtual doctor consultations, remote learning, and virtual private network (VPN) connections for employees working from home became more prevalent. This paradigm shift has brought about positive benefits, however, it has also increased the attack vectors and surface, creating lucrative opportunities for cyber-attacks. Consequently, more sophisticated attacks have emerged, including Botnet attacks which typically lead to distributed Denial of Service (DDoS). These pose a serious threat to businesses and organisations worldwide. This paper proposes a system for detecting malicious activities in network traffic using sequential pattern mining (SPM) techniques. The proposed approach utilises SPM as an unsupervised learning technique to extract intrinsic communication patterns from network traffic, enabling the discovery of rules for detecting malicious activities and generating security alerts accordingly. By leveraging this approach, businesses and organisations can enhance the security of their networks, detect malicious activities including emerging ones, and thus respond proactively to potential threats. The performance evaluation for the proposed approach reveals a True Positive Rate (TPR) of over 99% and a False Positive Rate (FPR) of 0%.

关键词： Intrusion Detection System

来源：评论

学校读者我要写书评

暂无评论

An Overview of Adaptive Network Control in the Internet of Things: Machine Learning Methods for Optimizing Traffic and Dynamic Resource Management

An Overview of Adaptive Network Control in the Internet of T...

引用

Data Science and Business systems (ICDSBS), international conference on

作者： A Karthikeyan J Joel Department of Electronics and Communication Engineering Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai Department of Computer Science and Engineering RMK Engineering College Chennai

ISBN: (数字)9798331585600

ISBN: (纸本)9798331585617

The Internet of Things (IoT) ecosystem has witnessed exponential growth, making network settings complex and dynamic. These challenges in energy efficiency, traffic, and resource allocation have already made adaptive network control an indispensable instrument for Internet of Things (IoT) systems. The survey provides a comprehensive overview of adaptive network control techniques, particularly those based on ML algorithms to maximize traffic handling and dynamic resource allocation. Focusing on Internet of Things (IoT) use cases such as edge computing, sensor networks, and heterogeneous device management, the research examines a wide variety of ML algorithms, including supervised, unsupervised, and reinforcement learning. The study shows that network scaling using ML-based methods will be stable and load-balanced and reduce latency continuously. Here adaptive resource management is explored with reinforcement learning (RL) methods that can alter on-demand storage, processing and bandwidth to match the dynamic requirements. It says federated learning provides a way to optimize decentralized systems without compromising user data while making full use of distributed resources. Recent studies from the wide spectrum of ML applications provide case studies and experimental findings for increasing fault tolerance, reducing energy consumption, and improving Quality of Service (QoS) in IoT networks. Enabling flexible, efficient, and sustainable IoT networks, this study presents the transformative potential of machine learning. Other important research issues identified include scalable algorithms, real-time decision-making abilities, and high security. Suggestions for future work reveals the area of hybrid ML models, 6G AI convergence and development of light weight algorithms that can be run in low power Internet of Things devices. This work aims to provide a foundation for researchers and practitioners to use machine learning for advanced network control in the context of

关键词： Adaptive systems Machine learning algorithms Federated learning Scalability Heuristic algorithms Reinforcement learning Quality of service Dynamic scheduling Internet of Things Resource management

来源：评论

学校读者我要写书评

暂无评论

Keynote Speech 2 Towards a Continuum Computing Framework for Decentralised Federated Learning Based Context-aware IoT Applications

Keynote Speech 2 Towards a Continuum Computing Framework for...

引用

international conference on Social networks Analysis, Management and security (SNAMS)

作者： Nabil Abdennadher University of Applied Sciences Western Switzerland

ISBN: (数字)9798331518349

ISBN: (纸本)9798331518356

The proliferation of sensing device technologies, and the growing demand for data-intensive loT applications, are paving the way to the next wave of transformation in IoT computing systems architecture. The goal today is to design, implement and deploy a seamless interconnection of IoT, edge, cloud and High-Performance Computing (HPC) resources in one computing system, to form a compute continuum, also referred to as edge-to-cloud. In this talk, continuum computing refers to the deployment and execution of context-aware machine learning-based applications employing IoT sensors. Because of their distributed nature over constrained resources devices, these applications leverage the cloud and HPC infrastructures for learning tasks while exploiting edge devices for inference tasks on data coming from local IoT sensors. But the next wave is already underway; it will involve designing edge-to-edge platforms where learning takes place locally while a coordination platform enables edge devices to share their intelligence. This talk will cover the following points: 1. why and what is continuum computing? 2. A comparative study of centralised continuum computing solutions available on the market, where the edge intelligence is controlled by the Cloud, 3. A decentralised continuum computing framework deployed on edge-to-edge infrastructure and supporting decentralised federated learning (DFL). Here, the edges improve their intelligence by exchanging with their “neighbours”, 4. An example of a DFL based context-aware IoT application, for energy sector, deployed on a decentralised continuum computing platform. This talk is the result of two European projects: SWARM and LASAGNE Keywords- continuum computing, edge-to-cloud, edge-to-edge, context-aware IoT applications, federated learning.

关键词： Internet of Things Federated learning computer science Europe systems architecture Social networking (online) Smart cities security Reliability Intelligent sensors

来源：评论

学校读者我要写书评

暂无评论

A Mutual Intrusion Detection System for MANET to Address DDoS attacks using Data Mining Techniques

A Mutual Intrusion Detection System for MANET to Address DDo...

引用

Sustainable Computing and Data Communication systems (ICSCDS), international conference on

作者： K. Bala P N Renjith M Latha. S.T. Santhanalakshmi Department of Computer Science and Engineering School of Computing Bharath Institute of Higher Education and Research Chennai Tamilnadu India Department of Computer Science and Engineering VIT Chennai Campus Chennai Tamilnadu India Department Of Information Technology Ramapuram Campus SRM Institute of Science and Technology Chennai Tamilnadu India Department of Computer Science and Engineering Panimalar Engineering College Chennai Tamil Nadu India

A type of wireless communication network called a mobile ad hoc network (MANET) is composed of numerous flexible components that can move in any of the network’s many directions. The Intrusion Detection System (IDS) is a systematic tool implemented to spot suspicious activity with network malfunctions and sends an alert to the security control center. A malicious effort to interfere with the server’s or networks regular operation is acknowledged as a distributed denial-of-service (DDoS). This occurrence causes the networking system’s general performance to decline. Certain measures must be put into place to improve efficiency. These DDoS attacks are classified as application layer attacks, protocol attacks, and volumetric attacks in the networking system. The server experiences downtime as a result, and the network’s general performance suffers. When resources are brought back into the network, it causes external tension. Data mining methods can be used to find this and fix it.

关键词： Wireless communication Systematics Protocols Intrusion detection Data mining Servers security

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of a 5G security Testbed Based on Zero Trust Architecture

Design and Implementation of a 5G Security Testbed Based on ...

引用

international conference on Information and Communication Technology Convergence (ICTC)

作者： Mahnsuk Yoon Jihun Seo Jonghoon Lee Keuchul Cho Future Mobile Communication Research Center GERI(Gumi Electronics & Information Technology Research Institute) Gumi Korea Department of The Fourth Industrial Revolution & Transport Center for Connected & Automated Driving Research Korea Transport Institute Sejong Korea Cyber Security Research Division ETRI(Electronics and Telecommunications Research Institute) Daejeon Korea School of Computer Secience and Engineering Software Education Center Kyungpook National University Daegu Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

This paper presents the design and implementation of a 5G security testbed based on Zero Trust Architecture (ZTA). As 5G networks offer ultra-high speeds, low latency, and massive connectivity, ensuring their security has become a critical challenge, especially with the distributed nature and numerous connected devices. Traditional perimeter-based security models are no longer sufficient. Therefore, Zero Trust Architecture, which continuously verifies and monitors all resources and users regardless of their location, has been proposed as a solution. In this study, we propose a comprehensive security management system by integrating ZTA into a 5G testbed, focusing on real-time monitoring and dynamic policy enforcement using data collected from the Access and Mobility Management Function (AMF) and User Plane Function (UPF). The testbed's effectiveness is demonstrated through the deployment of Nokia's network equipment, allowing the collection and analysis of high-resolution traffic data, which aids in early threat detection and response. The proposed system enhances 5G network security and offers significant potential for application across various industries.

关键词： 5G mobile communication security management Architecture Network security Real-time systems Threat assessment Zero Trust security Low latency communication Monitoring

来源：评论

学校读者我要写书评

暂无评论

Autoencoder-based Temporal Convolutional Network for Real-Time Anomaly Detection in Large-Scale Network Traffic

Autoencoder-based Temporal Convolutional Network for Real-Ti...

引用

distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE international conference on

作者： Rana Veer Samara Sihman Bharattej R Raed Hamyd Mamatha Bai B G Sandeep Reddy Sasikumar Gurumoorthy Doctorate of Business Administration National Louis University FL USA Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Science and Engineering Nitte Meenakshi Institute of Technology Bengaluru India School of Computer Science and Engineering Malla Reddy Engineering College for Women (UGC-Autonomous) Hyderabad India Department of Computer Science and Engineering School of Engineering and Technology Dhanalakshmi Srinivasan University Tiruchirappalli India

ISBN: (数字)9798331533663

ISBN: (纸本)9798331533670

Nowadays, the rapid growth of network traffic has needed the development of efficient anomaly detection systems to ensure network security and reliability. However, the existing One-Class Support Vector Machine (One-class SVM) model often relay on manual feature engineering which was led to time-consuming and ineffective in detecting unknown threats. Hence, this research proposes an Autoencoder-based Temporal Convolutional Network (AE-TCN) for real-time anomaly detection in large-scale network traffic data. This process begins with the collection of input data from Coburg Intrusion Detection Data Set (CIDDS-001) dataset which consists of real time network traffic data from an internal server and external server. Then, the input data is preprocessed with the help of one-hot encoding to convert the categorical variables into numerical variables. After that, Recursive Feature Elimination (RFE) is employed to select the features namely class label, packets and type of attack by eliminating the irrelevant features from the input data. Finally, AE-TCN is introduced to identify the anomalies in large-scale network traffic data from reconstructed nominal patterns. From the results, the proposed AE-TCN achieved better results in terms of accuracy (99.98%), precision (99.95%), recall (99.26%), and F1 score (99.63%) respectively when compared to existing Convolutional Neural Network (CNN) model.

关键词： Support vector machines Autoencoders Telecommunication traffic Manuals Feature extraction Real-time systems Convolutional neural networks Servers Relays Anomaly detection

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 << < 89 90 91 92 93 94 95 96 97 98 > >>

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：