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

4,997 篇 会议
280 册 图书
88 篇 期刊文献

馆藏范围

5,365 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,884 篇 工学
- 2,574 篇 计算机科学与技术...
- 1,725 篇 软件工程
- 970 篇 信息与通信工程
- 371 篇 电气工程
- 307 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...
- 120 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
617 篇 理学
- 371 篇 数学
- 118 篇 生物学
- 105 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

499 篇 security
355 篇 wireless sensor ...
309 篇 computer network...
253 篇 protocols
247 篇 computer archite...
216 篇 intrusion detect...
213 篇 authentication
210 篇 computer communi...
200 篇 ip networks
189 篇 computer crime
171 篇 servers
165 篇 computer securit...
158 篇 information secu...
156 篇 network security
151 篇 internet of thin...
151 篇 distributed comp...
147 篇 computer science
147 篇 cryptography
142 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...
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...
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

17 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 mukaddim pathan
7 篇 osvaldo gervasi
7 篇 yanmin zhu
7 篇 mohammad s. obai...
7 篇 barolli leonard
7 篇 lin zhang
7 篇 jasni mohamad za...
7 篇 wei wang
6 篇 klaus wehrle
6 篇 zarai faouzi
6 篇 yunhao liu
6 篇 shahid raza

语言

5,191 篇 英文
143 篇 其他
39 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 5365 条记录，以下是771-780 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：

Deep Learning-Based DDoS Attack Detection Using Adversarial Optimization

Deep Learning-Based DDoS Attack Detection Using Adversarial ...

引用

IEEE international conference on Trust, security and Privacy in Computing and Communications (TrustCom)

作者： Dahai Yu Jianming Cui Yungang Jia Peiguo Fu Ming Liu School of Information Engineering Chang’an University Xi’an China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing China

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

In the field of cybersecurity, increasingly emerging network threats seriously affect the security of network and users. Notably, DDoS attacks represent a critical concern due to their capacity to inundate and debilitate targeted systems via distributed networks. This study introduces a DDoS attack detection framework employing a dual-detection model designed to identify both conventional and adversarial DDoS attacks. Adversarial DDoS attacks are characterized by their enhanced capability to circumvent standard DDoS detection mechanisms. The proposed framework incorporates an optimized CNN architecture for the detection of traditional DDoS attacks. This optimization involves substituting fully connected layers with global average pooling layers, an approach validated through comparative experimentation to yield the most effective base CNN model. For the detection of adversarial DDoS attacks, we propose a new detection algorithm, in which methodology initially employs the WGAN-GP data generation process to create synthetic DDoS attack data, followed by the strategic alteration of certain feature values within the generated attack data using normal traffic data. The resultant perturbed data are then utilized to train the adversarial DDoS attack detection model. Empirical assessments performed on the CIC-IDS2017 and CIC-DDoS2019 datasets confirm the efficacy of the dual-detection model in accurately identifying both traditional and adversarial DDoS attacks, achieving an accuracy exceeding 95%.

关键词： Accuracy Denial-of-service attack Generative adversarial networks Feature extraction Real-time systems Data models Convolutional neural networks computer crime Detection algorithms Optimization

来源：评论

学校读者我要写书评

暂无评论

DNN Partitioning and Assignment for distributed Inference in SGX Empowered Edge Cloud

DNN Partitioning and Assignment for Distributed Inference in...

引用

international conference on distributed Computing systems

作者： Yuepeng Li Deze Zeng Lin Gut Song Guo Albert Y. Zomaya School of Computer Science China University of Geosciences Wuhan China Engineering Research Center of Natural Resource Information Management and Digital Twin Engineering Software Ministry of Education Wuhan China School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computing The Hong Kong Polytechnic University Hong Kong School of Computer Science The University of Sydney Australia

ISBN: (数字)9798350386059

ISBN: (纸本)9798350386066

distributed Deep Neural Network (DNN) inference is a promising technology to explore the distributed resources in edge cloud to realize edge intelligence. Meanwhile the inherent resource sharing nature of edge cloud infrastructure also raises serious concerns on security and privacy. Software Guard Ex-tensions (SGX) emerges as a potential hardware-level solution but its limited secure memory (i.e., enclave page cache) imposes new challenges, especially in contrast to memory-hungry DNN models. A task's performance will be severely affected when its memory footprint is beyond the enclave page cache size, due to expensive secure page swapping. In this case, how to appropriately partition a DNN model and assign the partitions to distributed edge servers to efficiently utilize edge resources for fast secure inference becomes a challenging problem. In this paper, we first show that this problem is NP-hard. We further propose a MEmory -aware distributed Inference Acceleration (MEDIA) algorithm, whose guaranteed approximation ratio is also formally analyzed. We have implemented a prototype system and applied some well-known representative DNN models to evaluate MEDIA's performance. Through extensive experiments, we verify the efficiency of MEDIA by the fact that it reduces the inference time by 19.5%-38.1 % in comparison with state-of-the-art approaches.

关键词： Computational modeling Prototypes Artificial neural networks Media Approximation algorithms Inference algorithms Software

来源：评论

学校读者我要写书评

暂无评论

CT-PBFT: A Comprehensive Trust-Based Practical Byzantine Consensus Algorithm

CT-PBFT: A Comprehensive Trust-Based Practical Byzantine Con...

引用

international conference on computer and Communications (ICCC)

作者： Yufei He Siyuan Du Shuaifan Xia Yingkang Zhong Qingwen Liu Chunqi Tian Wen Fang Mingliang Xiong College of Computer Science and Technology Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China College of Electronic and Information Engineering Tongji University Shanghai China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

Blockchain technology has become a foundational component for constructing decentralized, secure, and immutable distributed systems. The consensus mechanism ensures that all nodes in a blockchain network reach agreement on a single version of truth, thereby maintaining data consistency across the distributed ledger. The earliest blockchain application, Bitcoin, adopts Proof of Work (PoW), which provides high security at the cost of substantial computational power and energy consumption. Ethereum employs Proof of Stake (PoS) to reduce energy consumption, though it introduces new challenges in the fairness of node selection. Practical Byzantine Fault Tolerance (PBFT) has gained significant attention for its ability to achieve more efficient consensus by reducing computational and energy demands. However, traditional PBFT still requires extensive message exchanges and voting among nodes, leading to significant communication overhead in large-scale networks. To address these limitations and further enhance the performance of PBFT, we propose the Comprehensive Trust-based PBFT (CTPBFT) algorithm. CT-PBFT reduces communication overhead by excluding nodes with low trust scores from the consensus process, thereby optimizing overall efficiency. We conducted a thorough analysis and simulation of CT-PBFT, and the results demonstrate that CT-PBFT outperforms traditional PBFT in terms of consensus latency and throughput. Moreover, CT-PBFT is more effective than other trust-based PBFT variants in swiftly eliminating Byzantine nodes, providing a robust and efficient solution for secure communication in distributed systems.

关键词： Energy consumption Proof of stake Fault tolerance distributed ledger Fault tolerant systems Consensus algorithm Throughput Proof of Work Blockchains Consensus protocol

来源：评论

学校读者我要写书评

暂无评论

SPM-GCN: An adaptive reordering algorithm for sparse LU factorization via GCN

SPM-GCN: An adaptive reordering algorithm for sparse LU fact...

引用

international conference on Parallel and distributed systems (ICPADS)

作者： Min Tian Huazeng Liu Junjie Wang Qi Liu Wei Du Zanjun Zhang Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Key Laboratory of Computing Power Network and Information Security Qilu University of Technology (Shandong Academy of Sciences) Jinan Key Laboratory of High Performance Computing Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Shaanxi Key Laboratory of Large Scale Electromagnetic Computing Xidian University Xi’an China

Sparse LU factorization is a critical kernel in scientific computing and engineering applications. A better nonzero pattern of sparse matrixes can accelerate LU factorization by reordering. Traditionally it’s difficult to predict which non-zero pattern is optimal for a sparse matrix. In this paper, we proposed a graph convolutional neural network (GCN) for adaptively selecting the optimal reordering algorithm from five candidate reordering algorithms in the Matrix preprocessing step, referred to as SPM-GCN. After using our SPM-GCN, the average numerical factorization time outperformed the other five algorithms, and the average numerical factorization time was reduced by 17.3% compared with the default method of swSuperLU.

关键词：

来源：评论

学校读者我要写书评

暂无评论

LDVNet: Lightweight and Detail-Aware Vision Network for Image Recognition Tasks in Resource-Constrained Environments

LDVNet: Lightweight and Detail-Aware Vision Network for Imag...

引用

international conference on Parallel and distributed systems (ICPADS)

作者： Yuchen Liu Hu Liang Ran Qiu Shengrong Zhao Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China

In many underwater application scenarios, recognition tasks need to be executed promptly on computationally limited platforms. However, models designed for this field often exhibit spatial locality, and existing works lack the ability to capture crucial details in images. Therefore, a lightweight and detail-aware vision network (LDVNet) for resource-constrained environments is proposed to overcome the limitations of these approaches. Firstly, in order to enhance the accuracy of target image recognition, we introduce transformer modules to acquire global information, thus addressing the issue of spatial locality inherent in traditional convolutional neural networks (CNNs). Secondly, to maintain the network’s lightweight nature, we integrate the transformer module with convolutional operations, thereby mitigating the substantial parameter and floating point operations (FLOPs) overhead. Thirdly, for the efficient extraction of crucial fine-grained details from feature maps, we have devised a channel and spatial attention module (C&SA). This module aids in recognizing intricate and fine-grained visual tasks and enhances image understanding. It is seamlessly integrated into LDVNet with nearly negligible parameter overhead. The experimental results demonstrate that LDVNet outperforms other lightweight networks and hybrid networks in different recognition tasks, while being suitable for resource-constrained environments.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Blockchain-Enhanced AI Diagnostics in Healthcare

Blockchain-Enhanced AI Diagnostics in Healthcare

引用

Emerging Technologies and Innovation for Sustainability (EmergIN), international conference on

作者： Sachin Pal Tanushka Kanishka Jha Deepika Sharma Department of Computer Science and Engineering Chandigarh University Mohali India Department of Computer Science and Engineering Banasthali Vidhyapith Tonk Rajasthan India Department of Computer Science and Engineering Chandigarh University Mohali Punjab India

ISBN: (数字)9798350391268

ISBN: (纸本)9798350391275

The integration of advanced diagnostic systems and Blockchain technology offers a transformative opportunity to revolutionize healthcare by improving accuracy, enhancing data security, and enabling efficient, patient-centric care. Intelligent diagnostic systems have shown significant potential in analysing complex medical data, detecting patterns, and facilitating faster, more precise diagnoses. However, challenges related to the privacy, security, and interoperability of sensitive healthcare data continue to hinder widespread adoption of innovative technologies in healthcare. In this context, Blockchain technology provides a decentralized, transparent, and tamper-resistant solution for secure data sharing and management. This paper explores how Blockchain can enhance healthcare diagnostic systems by ensuring the integrity, confidentiality, and traceability of medical records. By utilizing Blockchain's distributed nature, patient data can be securely shared across healthcare providers without compromising privacy, mitigating the risk of data breaches, and ensuring compliance with stringent regulatory frameworks. Blockchain enables the secure aggregation and analysis of healthcare data, leading to improved diagnostic accuracy and reduced medical errors. Additionally, Blockchain facilitates the use of smart contracts, automating healthcare processes such as insurance claims, treatment workflows, and compliance monitoring, further streamlining patient care. We examine the technical architecture of Blockchain-enabled healthcare systems, analyzing key benefits such as enhanced data integrity, real-time access to patient information, and decentralization of healthcare networks.

关键词： Data privacy Technological innovation Accuracy Data security Smart contracts Medical services Data breach Blockchains Sustainable development Medical diagnostic imaging

来源：评论

学校读者我要写书评

暂无评论

Vulnerability Assessment of security Breach and Deadly Threat in Cloud Computing Environment

Vulnerability Assessment of Security Breach and Deadly Threa...

引用

international conference on Computational Intelligence and Communication networks (CICN)

作者： Ashish Gupta Shreya Sinha Harsh Kumar Singh Bharat Bhushan Computer Science and Engineering Sharda University Greater Noida India

Cloud computing allows us to access available systems and pay for what we require whenever needed. When there is access to the internet, it uses some techniques like Service-Oriented Architecture (SOA), virtualization, distributed computing, etc. Cloud computing has transformed the way people utilize and handle computer services. It enables sharing, pooling, and accessing resources on the Internet. It offers tremendous advantages that enhance the cost-effectiveness and efficiency of organizations, which is marked by security challenges or threats that can compromise data, service safety and privacy. This paper gives an overview of cloud computing and explores the threats and vulnerabilities related to cloud computing with its countermeasures. It also explores the recent advancement in cloud computing threats and countermeasures. Further, this paper highlights the case studies on recent attacks and vulnerabilities which are compromised. Finally, this paper concludes that cloud computing is efficiently used to mitigate the threats and vulnerabilities with its countermeasures.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Role of IoT in Enhancing Wireless Sensor Network Applications: A Comprehensive Analysis

The Role of IoT in Enhancing Wireless Sensor Network Applica...

引用

Emerging Trends in Engineering and Medical Sciences (ICETEMS), international conference on

作者： Sonia Singh Neha Gupta School of Computer Applications Manav Rachna International Institute of Research & Studies Faridabad India

ISBN: (数字)9798331529352

ISBN: (纸本)9798331529390

WSNs are a system of spatially distributed sensors that sense some environmental phenomena and communicate the information without wires to a central system. Now, integration with the IoT further strengthens WSNs in aspects such as real-time data collection, analysis, and decision making across diverse network applications, fueling innovation in smart environments. Wireless Sensor networks (WSNs) are normally groups of sensors that gather information about their surroundings and transmit it to the main system without the use of wires. The role of the Internet of Things in WSN is to provide an avenue through which the data from the sensors can be shared in real-time, hence making smart systems efficient and responsive This paper present a qualitative research paradigm where systematic literature survey has been conducted on many articles in which IoT based WSN articles published in the last five years along with a qualitative analysis of performance indicators of 20 real-world IoT-enhanced WSNs. The findings reveal that IoT integration significantly improves WSN capabilities in three key areas: It has achieved (1) network longevity, which is a 40% increase in overall sensor lifespan; (2) data accuracy, with the observation that it has cut down on false positives by 25%; and (3) real-time responsiveness, which has proven to have truncated the delay in data transmission by 60%. Nevertheless, we also pinpoint the threats in the security and privacy domains, where 75% of investigated systems are vulnerable to cyber threats. The researchers establish that IoT greatly accelerates the WSN applications in smart city and environment monitoring, but this comes with the need to enforce better security and standardized procedures for optimal use of IoT in achieving the WSN application goals. This research therefore offers a systematic map for researchers and practitioners to foster the integration of IoT in WSN applications towards intelligent and reliable sensor networks in the

关键词： Wireless sensor networks Systematics Wires Smart systems Real-time systems Sensor systems Sensors security Internet of Things Intelligent sensors

来源：评论

学校读者我要写书评

暂无评论

Scalable and Adaptive Intrusion Detection in Cloud Environments Using Machine Learning with CIML-IDS

Scalable and Adaptive Intrusion Detection in Cloud Environme...

引用

Next Generation Communication & Information Processing (INCIP), international conference on

作者： Uma Reddy Yagateela Pandu Rangaiah Amandeep Nagpal Abhishek Kaushik Mustafa Abdulhussein Al-Allak Department of Artificial Intelligence and Machine Learning N.H. College of Engineering Bangalore India Department of Electronics and Communication Enfineering Institute of Aeronautical Engineering Dundigal Hyderabad India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Greater Noida Uttar Pradesh College of Medical Technology The Islamic University Najaf Iraq

ISBN: (数字)9798331528140

ISBN: (纸本)9798331528157

The combination of Machine Learning (ML) with Network Intrusion Detection systems (NIDS) can be considered a revolutionary step that took place in the sphere of network security especially when implemented in cloud environment. The present research study focuses on the CIML-IDS that the author has personally developed as a machine learning-based IDS for large cloud networks to identify security threats in real-time. CIML-IDS is highly efficient in terms of detecting existing as well as unknown patterns of intrusion using Random Forest, Gradient Boosting, and Deep Neural networks. But with the cloud deployment, resource utilization and its ability to operate under different loads and across distributed domains is made possible. The design of the proposed CIML-IDS includes feature extraction as a prerequisite for real-time anomalous activity detection, which increases the system's adaptability. Moreover, principles of the secure cloud computing enhance the integrity and the confidentiality of data, States that may act as the drawbacks of the cloud infrastructure. Efficient empirical tests carried out on the benchmark datasets corroborate the high detection rates of CIML-IDS and low false positive observations. The studies summarize the possibility of improving the usage of ML-based NIDS in enhancing the cloud network security and creating a robust defence system against novel threats.

关键词： Cloud computing Network intrusion detection Telecommunication traffic Information processing Network security Feature extraction Real-time systems Resource management computer security Random forests

来源：评论

学校读者我要写书评

暂无评论

University distributed computer Network Vulnerability Assessment

University Distributed Computer Network Vulnerability Assess...

引用

Smart Information systems and Technologies (SIST), IEEE international conference on

作者： Valerii Lakhno Volodimir Malyukov Bakhtyzhan Akhmetov Bagdat Yagaliyeva Olena Kryvoruchko Alona Desiatko Department of Computer Systems Networks and Cybersecurity National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Informatics and Informatization of Education Abai Kazakh National Pedagogical University Almaty Kazakhstan Department of Computer Sciences Yessenov University Aktau Kazakhstan Department of Software Engineering and Cybersecurity State University of Trade and Economics Kyiv Ukraine

A methodology for evaluating information security (IS) for a distributed computer network (DCN) of a university (hereinafter referred to as UDCN) has been proposed. A mathematical model for calculating the UDCN vulnerability factor has been presented. The UDCN vulnerability coefficient makes it possible to assess its IS level at the UDCN design stage. The results of simulation modeling and virtualization of IS UDCN components have also been presented. In the course of simulation modeling, a model of a protected UDCN was designed and tested. In the experimental UDCN model, the network devices selected in the course of modeling the vulnerability coefficient were emulated on virtual machines (VMs). UDCN resources were reproduced using the Proxmox VE virtualization system. On the UDCN hosts running PVE, the Suricata Intrusion Detection System (IPS) was used. Splunk was used as SIEM.

关键词：

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 << < 74 75 76 77 78 79 80 81 82 83 > >>

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：