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

4,981 篇 会议
280 册 图书
87 篇 期刊文献

馆藏范围

5,348 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,872 篇 工学
- 2,564 篇 计算机科学与技术...
- 1,719 篇 软件工程
- 966 篇 信息与通信工程
- 369 篇 电气工程
- 301 篇 控制科学与工程
- 180 篇 网络空间安全
- 125 篇 动力工程及工程热...
- 124 篇 电子科学与技术（可...
- 120 篇 安全科学与工程
- 110 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
613 篇 理学
- 367 篇 数学
- 118 篇 生物学
- 104 篇 系统科学
- 100 篇 统计学（可授理学、...
- 84 篇 物理学
484 篇 管理学
- 334 篇 管理科学与工程(可...
- 187 篇 图书情报与档案管...
- 159 篇 工商管理
241 篇 法学
- 165 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
14 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
188 篇 computer crime
171 篇 servers
164 篇 computer securit...
158 篇 information secu...
154 篇 network security
151 篇 distributed comp...
150 篇 internet of thin...
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

5,231 篇 英文
86 篇 其他
38 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 5348 条记录，以下是81-90 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：

Method for Filtering DDoS Attack Traffic through Routing Path within SDN Domain

Method for Filtering DDoS Attack Traffic through Routing Pat...

引用

IEEE international conference on Big Data security on Cloud (BigDatasecurity), High Performance and Smart Computing (HPSC) and Intelligent Data and security (IDS)

作者： Meng Yue Mingzhi Yang Hanwen Xu Zhijun Wu College of Safety Science and Engineering Civil Aviation University of China Tianjin China

ISBN: (数字)9798331595104

ISBN: (纸本)9798331595111

Attacks that aim to disrupt services, known as distributed Denial of Service (DDoS), exploit protocol vulnerabilities and utilize legitimate traffic to target systems, thereby threatening the normal operation of the network. This paper proposes a method for filtering DDoS attack traffic along routing paths within the Software Defined Networking (SDN) domain. The method, based on the SDN framework, employs a consistency hashing algorithm to select nodes in the global routing platform, forming secure access paths. By utilizing the accuracy of edge node detection and inter-domain cooperation, the attack is effectively mitigated along the path close to its origin, which is referred to as path filtering. The paper also provides a design for the filtering framework and details the filtering steps.

关键词： Filtering Image edge detection Collaboration Routing Denial-of-service attack Vectors Consensus protocol IP networks computer crime Software defined networking

来源：评论

学校读者我要写书评

暂无评论

MultiMal: Multimodal Fusion Combining Graph and Entropy Features for Malware Detection

MultiMal: Multimodal Fusion Combining Graph and Entropy Feat...

引用

IEEE international conference on Software Analysis, Evolution and Reengineering (SANER)

作者： Kaiyan He Haining Lu Dawu Gu Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331535100

ISBN: (纸本)9798331535117

As software becomes widespread, malware poses a significant threat to information system security. Graph neural networks (GNNs) used in existing machine learning-based methods for malware detection ignore deeper semantic information in code graphs. These methods also lack feature extraction of global data information, resulting in incomplete feature for detection. To address these limitations, we propose a multi-modal fusion architecture, MultiMal, that combines function call graphs, control flow graphs, and entropy features to detect Portable Executable (PE) malware. MultiMal proposes a multi-head softmax module to effectively capture graph features in multiple representation spaces. It also constructs an entropy-based learning module to extract binary features related to data randomness and obfuscation, which are then fused with the graph encoding to better detect malware code pattern. For accurate evaluation, we also introduce a new PE malware dataset with evenly distributed samples over the years and detailed family and category labels. Experiments demonstrate that MultiMal outperforms three existing baselines in terms of effectiveness. At an FPR threshold of 0.1 %, the TPR and bACC exceed the best results of the baselines by 11.83 % and 5.54 %, respectively.

关键词： Learning systems Codes Accuracy Semantics computer architecture Feature extraction Malware Entropy Graph neural networks security

来源：评论

学校读者我要写书评

暂无评论

Privacy-Preserving Publishing Mechanism for Real-Time Vehicle Trajectory in Vehicle-to-Grid networks

Privacy-Preserving Publishing Mechanism for Real-Time Vehicl...

引用

Power Electronics, computer Applications (ICPECA), IEEE international conference on

作者： Yulong Wang Jianbo Xu Bo Gong School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

The Vehicle-to-Grid (V2G) network is a smart grid technology generated under the background of the rapid development of new energy technology, which allows mobile energy storage vehicles (MESVs) to realize bidirectional energy exchange with the grid system. As distributed energy storage units within the V2G network, MESVs help meet the grid's load-balancing demands. To accurately schedule grid loads, V2G networks rely on MESVs' real-time trajectory data. After collecting this data, the central authority (CA) publishes it to the grid enterprise (GM) for load-balancing decisions. However, before publication, the CA must process the data to protect the location privacy of MESVs and prevent GM from extracting sensitive information. To address this privacy protection challenge during data publication, we propose a differential privacy-based mechanism. Our mechanism uses the unscented Kalman filter to predict and correct the published data at the sampling point and intelligently adjusts the sampling interval. Additionally, we introduce a privacy budget allocation method based on regional access frequency and travel time, enhancing privacy protection of trajectory in high-access areas and peak hours. Through security analysis and experimental validation, our mechanism effectively preserves the privacy of real-time vehicle trajectory data while ensuring data validity.

关键词： Vehicle-to-grid Data privacy Privacy Publishing Real-time systems Trajectory Kalman filters security Protection Radio spectrum management

来源：评论

学校读者我要写书评

暂无评论

Octopus: Experiences with a Hybrid Event-Driven Architecture for distributed Scientific Computing 24

Octopus: Experiences with a Hybrid Event-Driven Architecture...

引用

Proceedings of the SC '24 Workshops of the international conference on High Performance Computing, Network, Storage, and Analysis

作者： Haochen Pan Ryan Chard Sicheng Zhou Alok Kamatar Rafael Vescovi Valérie Hayot-Sasson André Bauer Maxime Gonthier Kyle Chard Ian Foster Department of Computer Science University of Chicago Chicago IL USA Data Science and Learning Division Argonne National Laboratory Lemont IL USA Department of Computer Science Southern University of Science and Technology Guangdong China Department of Computer Science Illinois Institute of Technology Chicago IL USA Department of Computer Science University of Chicago Chicago IL USA and Data Science and Learning Division Argonne National Laboratory Lemont IL USA

ISBN: (纸本)9798350355543

Scientific research increasingly relies on distributed computational resources, storage systems, networks, and instruments, ranging from HPC and cloud systems to edge devices. Event-driven architecture (EDA) benefits applications targeting distributed research infrastructures by enabling the organization, communication, processing, reliability, and security of events generated from many sources. To support the development of scientific EDA, we introduce Octopus, a hybrid, cloud-to-edge event fabric designed to link many local event producers and consumers with cloud-hosted brokers, and to provide a fabric for developing resilient applications. Octopus can be scaled to meet demand, permits the deployment of highly available Triggers for automatic event processing, and enforces fine-grained access control. We identify requirements in self-driving laboratories, scientific data automation, online task scheduling, epidemic modeling, and dynamic workflow management use cases, and present results demonstrating Octopus' ability to meet those requirements. Octopus supports producing and consuming events at a rate of over 4.2 M and 9.6 M events per second, respectively, from distributed clients.

关键词： Event-driven architecture

来源：评论

学校读者我要写书评

暂无评论

Advanced Machine Learning Approach for Cyber Attack Detection in Cloud Computing

Advanced Machine Learning Approach for Cyber Attack Detectio...

引用

Intelligent Control, Computing and Communications (IC3), international conference on

作者： Shashi Bhushan Singh Yadav Nitin Arvind Shelke Jagendra Singh Yasmeen Deependra Pandey Himanshi Department Computer Science & Engineering BBD Northern India Institute of Technology Lucknow India School of Computer Science Engineering & Technology Bennett University Greater Noida India Department of CSE-DS CVR College of Engineering Hyderabad India Department of ECE Amity School of Engineering and Technology Amity University Lucknow India Department of Information Technology Raj Kumar Goel Institute of Technology Ghaziabad India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

Cloud computing has become the most important part of modern IT infrastructure, which is scalable and flexible. However, with such wide-scale adoption, new vulnerabilities have been introduced into the system, making it a favorite target for cyber-attacks, especially distributed Denial-of-Service (DDoS) and Man-in-the-Cloud (MitC) attacks. security measures in cloud environments are more than ever required to be effective. This study introduces a state-of-the-art approach using machine learning techniques to identify and prevent such attacks; the four machine learning algorithms that have been used here are Support Vector Machine, Artificial Neural Network, Recurrent Neural Network, and k-Nearest Neighbors. A dataset of 3,200 simulated records has been used for the purpose of training and testing; 70% of data were used for training purposes, and 30% of data were used for testing purposes. The models were rated based on precision, running time, and memory usage. The results highlighted that SVM was the strongest model and had an accuracy of 97.86%, while ANN was about 93.4% followed by RNN which was about 89.45% and KNN at 86.7%. This would mean that among the above models, the SVM is the most efficient with respect to real-time attack detection as it is in high precision and has efficiency in resource use. The proposed approach can be very well applied to real-time cloud security systems, offering a robust solution in identifying and mitigating cyber threats in dynamic cloud environments, ensuring enhanced protection against evolving attack vectors.

关键词： Support vector machines Cloud computing Accuracy Recurrent neural networks Computational modeling Machine learning Artificial neural networks Nearest neighbor methods Real-time systems Cyberattack

来源：评论

学校读者我要写书评

暂无评论

Hashgraph-Based Model Parameter Management for Reliable and Secure Deep Learning

Hashgraph-Based Model Parameter Management for Reliable and ...

引用

IEEE international conference on Consumer Electronics (ICCE)

作者： Eunsung Roh Jinheock Choi Younghoon Park Seung-Woo Seo Big Data Research Center for New Value Creation Sookmyung Women's University Seoul South Korea Department of Electric Engineering Seoul National University Seoul South Korea Division of Computer Science Sookmyung Women's University Seoul South Korea

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Deep learning networks have rapidly developed across various fields, with several high-performing models already being applied in real-world applications. However, even with identical network architectures, variations in parameter values can lead to significantly different outputs, making the security of these parameters crucial for maintaining network performance. Despite their importance, limited research has focused on securing deep learning network parameters. In recent years, distributed ledger technologies, such as blockchain and hashgraph, have been extensively studied. Their applications extend beyond cryptocurrencies to include public services, voting, supply chains, and insurance. This paper proposes a novel approach to enhancing the security of deep learning network parameters by leveraging Hedera Hashgraph, providing a more secure foundation for their deployment and commercialization. With the security offered by hashgraph, model parameters are safely stored, ensuring the reliability and trustworthiness of deep learning systems. Additionally, when these stored parameters are used for further training, such as in transfer learning, the results are expected to be reliable. We demonstrate that our proposed system secures the parameters effectively, guaranteeing both security and reliability in deep learning.

关键词： Deep learning Training Transfer learning Supply chains Insurance Network architecture security Reliability History Software development management

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

Recent Trends in computer networks and distributed systems security 2012

引用

丛书名： Communications in computer and Information Science

2012年

作者： Sabu M. Thampi Albert Y. Zomaya Thorsten Strufe Jose M. Alcaraz-Calero Tony Thomas

ISBN: (数字)9783642341359

ISBN: (纸本)9783642341342

This book constitutes the refereed proceedings of the international conference on Recent Trends in computer networks and distributed systems security, held in Trivandrum, India, in October 2012. The 34 revised full papers and 8 poster presentations were carefully reviewed and selected from 112 submissions. The papers cover various topics in computer networks and distributed systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Bridging security and Efficiency: Energy-Aware Clustering for Data Encryption in Smart Agriculture

Bridging Security and Efficiency: Energy-Aware Clustering fo...

引用

international conference on Computing, Networking and Communications (ICNC)

作者： Huzaif Khan Lokesh Purohit Ali Jalooli Department of Computer Science California State University Dominguez Hills Carson CA USA

ISBN: (数字)9798331520960

ISBN: (纸本)9798331520977

Securing data communication in smart agriculture is essential to ensure data integrity and confidentiality in distributed sensor networks. While Cheon-Kim-Kim-Song (CKKS) homomorphic encryption offers strong security by allowing computation on encrypted data, its significant computational and energy overhead makes it unsuitable for energy-constrained devices like those in agricultural monitoring systems. We propose a novel framework to enable CKKS encryption in resource-limited settings through an optimized, energy-efficient clustering approach. By reducing the number of direct transmissions through data aggregation at cluster heads, our approach mitigates CKKS’s energy demands, making it feasible for low-power sensors. We formulate the clustering problem as an NP-hard optimization problem and present a real-time clustering algorithm that minimizes energy consumption while adapting to dynamic sensor energy levels. To evaluate our approach, we use the Gurobi optimizer to solve the problem to optimality and benchmark our algorithm’s performance. Results show that our solution achieves near-optimal energy efficiency, closely approximating the optimal solution while remaining computationally feasible for real-time applications. Additionally, our method improves packet delivery ratios and reduces end-to-end delay. This work provides a pathway for the practical implementation of advanced encryption schemes in energy-constrained environments.

关键词： Smart agriculture Energy consumption Heuristic algorithms Clustering algorithms Data aggregation Approximation algorithms Energy efficiency Real-time systems Reliability Homomorphic encryption

来源：评论

学校读者我要写书评

暂无评论

distributed Denial of Service Attack Detection by Machine Learning Techniques

Distributed Denial of Service Attack Detection by Machine Le...

引用

Learning and Technology conference (L&T)

作者： Varkha K. Jewani Prafulla E. Ajmire Mohd. Atique Bhisham Sharma Imed Ben Dhaou Suhashini Awadhesh Chaurasia Sant Gadge Baba Amravati University Amravati India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science Hekma School of Engineering Computing and Design Dar Al-Hekma University Jeddah Saudi Arabia Department of Computer Science RTM Nagpur University Nagpur

ISBN: (数字)9798331532215

ISBN: (纸本)9798331532222

The exponential expansion of computer networks and the internet makes it clear that there is a chance of being attacked and harmed. In the meantime, one of the most crucial defensive measures against the more complex and frequent network attacks is the intrusion detection and prevention systems (IDSs and IPSs). Due to insufficient datasets, anomaly-based research in intrusion detection systems is plagued by imprecise deployment, analysis, and evaluation. The researchers analyzed a variety of datasets, including DARPA98, KDD99, ISC2012, and ADFA13, to assess how well their suggested intrusion detection and intrusion prevention techniques performed. There are several issues: lack of adequate attack coverage, unrepresentative payloads, and anonymised packet information, insufficient traffic volume and diversity, or a deficiency in feature set and metadata. This study is focused on CICIDS-2017 which is the recently updated IDS dataset that meets real-world requirements and is accessible publicly. In addition to benign network flows and distributed denial of service (DDoS) attacks, it contains seven common attack network flows as well. To provide the optimal combination of features for the identification of the attack category, it also assesses the efficacy of several machine learning (ML) algorithms and network traffic feature sets. Even though various ML techniques like Linear Regression, Random Forests, and Decision Tree can be used, and performed very well, Hybrid Algorithm is designed to get better analysis on dataset.

关键词： Accuracy Machine learning algorithms Prevention and mitigation Linear regression Intrusion detection Training data Predictive models Decision trees computer crime Random forests

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 << < 5 6 7 8 9 10 11 12 13 14 > >>

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：