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

4,983 篇 会议
280 册 图书
87 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

2,872 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
165 篇 computer securit...
158 篇 information secu...
155 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

5,233 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 5350 条记录，以下是451-460 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：

Towards Smarter Maritime security: Apriori Algorithm Optimization in Serverless Environments 16

Towards Smarter Maritime Security: Apriori Algorithm Optimiz...

引用

16th international conference on Ambient systems, networks and Technologies networks, ANT 2025 / 8th international conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Shahin, Mahtab Rahimpour, Saeed Ghasempouri, Tara Bauk, Sanja Fahringer, Thomas Draheim, Dirk Estonian Maritime Academy Tallinn University of Technology Tallinn Estonia Department of Computer Systems Tallinn University of Technology Tallinn Estonia Distributed and Parallel Systems Group University of Innsbruck Tirol Austria Information Systems Group Tallinn University of Technology Tallinn Estonia

This paper presents an optimized implementation of the Apriori algorithm tailored for large-scale data mining in cloud-native, serverless environments, utilizing real-world fuel datasets. Our approach achieves a 28% reduction in execution time and a 22% decrease in memory consumption compared to traditional distributed Apriori methods. The study leverages high-dimensional fuel datasets, spanning from 2020 to 2050, to evaluate scalability and efficiency in processing energy-related data. By employing advanced synchronization and deferred partitioning strategies, communication overhead is significantly reduced, improving performance while effectively balancing computational loads across distributed nodes. security measures, including AES-256 encryption and role-based access control (RBAC), are incorporated to safeguard data confidentiality and ensure compliance with regulatory frameworks. The proposed solution scales efficiently for datasets up to 1 million records, demonstrating applicability across domains such as transportation and logistics. Future work will explore adaptive partitioning techniques, hybrid cloud architectures, and AI-driven predictive analytics to further enhance scalability and operational efficiency in serverless multi-cloud systems. © 2025 Elsevier B.V.. All rights reserved.

关键词： distributed cloud

来源：评论

学校读者我要写书评

暂无评论

Enhanced DDoS Detection using Machine Learning

Enhanced DDoS Detection using Machine Learning

引用

international conference on Information systems and computer networks (ISCON)

作者： Rashmikiran Pandey Mrinal Pandey Alexey Nazarov Department of Radio Engineering and Cybernetics Moscow Institute of Physics and Technology Moscow Russia Federal Research Center Computer Science and Control Russian Academy of Sciences Moscow Russia

The rapid growth of internet population poses a serious challenge to the security of internet resources. The security is directly affected by the hits of Denial of Services (DoS) attack which is rampant nowadays. With this evolving threat, designing a cutting-edge method is difficult from a cyber-security perspective. In this study, we propose a deep learning-based system for detecting distributed Denial of Service (DDoS) attacks, which utilizes Logistic Regression, K- Nearest Neighbor, and Random Forest algorithms. We assess proposed models using a recently updated NSL KDD dataset. Our research’s findings also demonstrate that proposed model is highly accurate in detecting distributed Denial of Service (DDoS) attacks. Our results show that our proposed model significantly improves upon current state-of-the-art attack detection methods

关键词： Machine learning algorithms Computational modeling Sociology Forestry Denial-of-service attack security computer crime

来源：评论

学校读者我要写书评

暂无评论

Fusion of Dynamic Hypergraph and Clinical Event for Sequential Diagnosis Prediction 29

Fusion of Dynamic Hypergraph and Clinical Event for Sequenti...

引用

29th IEEE international conference on Parallel and distributed systems, ICPADS 2023

作者： Zhang, Xin Peng, Xueping Guan, Hongjiao Zhao, Long Qiao, Xinxiao Lu, Wenpeng Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China Australian Artificial Intelligence Institute University of Technology Sydney Sydney Australia

ISBN: (纸本)9798350330717

Sequential diagnosis prediction (SDP) is a challenging task, aiming to predict patients' future diagnoses based on their historical medical records. While methods based on graph neural networks (GNNs) have proven successful for this task, they typically focus on modeling pairwise diseases using a global disease combination graph. However, these approaches neglect the fine-grained higher-order relations among persistent and emerging diseases within a single visit, which may contain crucial clues to predict the next diagnosis. Additionally, they fail to fully leverage patient-related clinical information present in electronic health records (EHRs). To address these challenges, this paper proposes a novel approach called the fusion of Dynamic Hypergraph and Clinical Event (DHCE) for sequential diagnosis prediction. The proposed method aims to exploit the fine-grained higher-order relations among diagnoses within a visit and leverage clinical event information from EHRs to improve the accuracy of predicting the next diagnosis. Specifically, DHCE categorizes diagnoses within a single visit in a fine-grained granularity into persistent and emerging categories based on a patient's historical diagnoses. It then constructs dynamic hypergraphs to capture higher-order disease relations within each visit. Next, we design a transition function to extract the transitional context from previous visits in order to generate the visit representation. Furthermore, to fully leverage patient-related clinical events in a visit, we utilize Bio-Clinical BERT to encode them and generate the clinical event representation for each visit. Finally, we combine the visit representation and event representation to generate a comprehensive patient representation, which is then used to predict the patient's next diagnosis. Experimental results on two benchmark datasets consistently demonstrate that DHCE outperforms state-of-the-art methods. © 2023 IEEE.

关键词： Bio-Clinical BERT clinical event dynamic hypergraph sequential diagnosis prediction

来源：评论

学校读者我要写书评

暂无评论

A Cooperative Feature Removal Mechanism for Cell Outage Detection in Wireless Telecommunication networks 19th

A Cooperative Feature Removal Mechanism for Cell Outage Det...

引用

19th international conference on Critical Information Infrastructures security, CRITIS 2024

作者： Wrona, Andrea Gentile, Simone De Santis, Emanuele Giuseppi, Alessandro Pietrabissa, Antonio Delli Priscoli, Francesco Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome via Ariosto 25 Lazio Rome00185 Italy Department of Electrical and Information Engineering Polytechnic of Bari via Re David 200 Puglia Bari70125 Italy

ISBN: (纸本)9783031842597

In the domain of crisis management for telecommunications infrastructures, the autonomous detection of cell outages within cellular networks is of paramount importance for prompt identification and resolution in ensuring uninterrupted connectivity to users. Traditional methods usually involve data aggregation at the core network, which is responsible for identifying cell failures. Proposing a novel approach, we leverage a Machine Learning-based distributed and cooperative feature removal mechanism in order to preserve the privacy of data and avoid any degradation in classification performance. Simulations carried out on a dataset retrieved from a real 4G-LTE rollout demonstrate that the proposed approach, through a cooperation among agents, maintains or even slightly improves accuracy, precision, recall, and F1-score in outage prediction compared to other conventional methods, showcasing its efficacy for cell outage detection purposes while maintaining data privacy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Robust Authentication Protocols for IoT Devices in High-Density networks

Robust Authentication Protocols for IoT Devices in High-Dens...

引用

distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： Senthilkumar Thangavel Arnav Kotiyal Ancy Thomas Harshal Patil Shirish Kulkarni Natrayan L Distributed Systems Cloud Solutions & Machine Learning Expert Paypal Inc California USA Department of Computer Science & Engineering Graphic Era Dehradun India Department of Computer Science and Engineering RNSIT Bangalore India School of Computer Science & Engineering IILM University Greater Noida India Department of Law Symbiosis Law School Symbiosis International (Deemed University) Pune India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Kuthambakkam India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Internet of things (IoT) gadgets have transformed several industries, including engineering, medicine, and more, thanks to the meteoric rise in the number of connected smart devices. The core principle of using the Internet of Things is that it expedites the delivery of information while consuming very little energy. In a nutshell, the Internet of Things (IoT) is a system of interconnected computing devices, services, and data that allows everyday objects to communicate with one another and with their physical environments. Prior to being saved on the server, all data sent across the IoT network must first be aggregated in the Queuing Telemetry Transport protocol (QTTP) broker. Access control, authorization, data storage, secrecy, authentication, system construction, and organization are some of the primary security concerns surrounding the Internet of Things (IoT). Three innovative security frameworks—RSA, Advanced Encryption Standard, and Elliptical Curve Cryptography—are created to enhance the protection of data in powered IoT devices. The security of IoT data is ensured by integrating all cryptic algorithms with the Constrained Queue Telemetry Transport Protocol (CQTTP). Data transmission from each IoT node undergoes cryptographic processes before being aggregated in the CQTTP. Exchange of key approvals, confirmation, and preservation of application data contrast are all accomplished by this cryptic action. Encryption keys are crucial to the safety of the data ix. The primary security component that reveals how many distinct key values a key in a protocol may take is the key's size. As a result, this study uses a new random key size method to give keys of varying sizes to the data sent by each node. Cryptography is harder when key sizes are set to be variable and random. In order to prevent script XSS commands and incorrect characteristics, all communications are encrypted using a technology that often permits employing TLS instead of plain TCP. Consequently, th

关键词： Transport protocols Wireless sensor networks Authentication Elliptic curve cryptography Encryption Internet of Things security Telemetry Smart devices Radiofrequency identification

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach: Biomedical Image Encryption for Healthcare Applications

A Novel Approach: Biomedical Image Encryption for Healthcare...

引用

distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： Kaparapu Satish Babu G. Sreelakshmi G. Vallathan S. Senthilkumar Department of ECE Geethanjali College of Engineering & Technology Hyderabad India Department of CSE Vinayaka Mission’s Kirupananda Variyar Engineering College Vinayaka Mission’s Research Foundation (DU) Salem India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

The rapid advancement in healthcare technology systems and transmission methods has enabled the acquisition, distribution, and management of data across medical devices, greatly enhancing traditional hospital information systems (HIS) to provide efficient healthcare services. However, transmitting medical information via wireless networks presents a significant risk of data tampering. Therefore, physicians must verify the integrity of received medical images before examining patients. To address this, a futuristic telehealth framework has been proposed to ensure security while offering comprehensive healthcare services at reduced costs. This paper introduces a framework that combines two modules: padding and Hyperchaotic 2D Logistic-Gaussian Map encryption, to enhance the security of patient medical data and scan images. The algorithm uses permutation, diffusion, and substitution operations to introduce effective confusion and diffusion in image pixels. The proposed approach is evaluated and compared with existing methods like ECC and Chaotic map encryption using MRI/CT medical images. Results show that the proposed framework provides robustness security, quality, and reliability, reducing the risk of misdiagnosis in telemedicine applications.

关键词： Correlation Medical devices Telemedicine Wireless networks Elliptic curve cryptography Prediction algorithms Robustness Encryption Protection Biomedical imaging

来源：评论

学校读者我要写书评

暂无评论

A Scalable Blockchain-Based Trust Management Strategy for Vehicular networks 17th

A Scalable Blockchain-Based Trust Management Strategy for Ve...

引用

17th international conference on Wireless Algorithms, systems, and Applications (WASA)

作者： Li, Minghao Zhao, Gansen Lai, Ruilin South China Normal Univ Sch Comp Sci Guangzhou 510631 Peoples R China

ISBN: (纸本)9783031192104;9783031192111

In recent years, the dynamic environment on the Internet of Vehicles led vehicular communication networks' trust management mechanism to become a research hotspot. Most of the existing trust management in vehicular networks relies on a centralized third party. However, it causes trust management to be limited to a single node and has high requirements for device performance. In order to improve the reliability of information exchanged between vehicles, we propose a scalable blockchain-based trust management strategy, which employs vehicle-related objective factors to evaluate the credibility of information transmitted between vehicles to determine the vehicles' trust level. We also design a consensus mechanism to make all RSUs (Roadside Units) maintain a consistent and reliable distributed ledger as nodes so that vehicles can obtain global trust information more quickly during interaction to improve its reliability. The security and performance analysis shows that our strategy has high reliability and availability.

关键词： Blockchain Vehicular networks Trust management Consensus mechanism

来源：评论

学校读者我要写书评

暂无评论

Blockchain based Secure and Effective Authentication Mechanism for 5G networks 1

Blockchain based Secure and Effective Authentication Mechani...

引用

1st IEEE international conference on Blockchain and distributed systems security, ICBDS 2022

作者： Bala, R. Manoharan, R. Puducherry Technological University Dept. of Computer Science and Engineering Puducherry India

ISBN: (数字)9781665428323

ISBN: (纸本)9781665428323

5G technology's rapid development revolutionized the field of cellular networks by providing higher data rate up to 10 Gbit/s using millimetre waves. Though 5G network can carry huge data with a higher speed than 4G, it can cover only a shorter province, around 1000 feet which is not even 2% of 4G's coverage. Numerous 5G cell towers and antennas are required to ensure reliable 5G signal and connectivity. This resulted in frequent and increased authentication when User Equipment (UE) moves between cells. Therefore, there is a critical need for a fast and frequent authentication mechanism. Though existing 4G authentication protocols can be adopted for 5G, they can only satisfy the basic requirements on the security front but cannot handle frequent authentications effectively. Blockchain technology with the features such as security, anonymity, immutability and transparency has been considered a promising technology to evade redundant authentications. Therefore, an effective and secure authentication scheme by completely utilizing features of Blockchain technology has been proposed in this paper. The proposed methodology works in two steps, the first by the introduction of a novel optimized authentication specific consensus algorithm for improving the Authentication Rate. Second, the reduction of the authentication by utilizing the authentication results stored in UE-AP Blockchain aiming to handle the redundant authentications. © 2022 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Binary Malware Detection via Heterogeneous Information Deep Ensemble Learning 29

Binary Malware Detection via Heterogeneous Information Deep ...

引用

29th IEEE international conference on Parallel and distributed systems, ICPADS 2023

作者： Song, Runhan Li, Lun Cui, Lei Liu, Qiqi Gao, Jin Chinese Academy of Sciences Institute of Information Engineering Beijing China University of Chinese Academy of Sciences School of Cyber Security Beijing China Zhongguancun Laboratory Beijing China

ISBN: (纸本)9798350330717

Dynamic malware detection refers to detecting mal-ware by inferring the run-time trace of malware, i.e., a sequence of API calls. In this paper, we proposed HeteroNet, a novel dynamic malware detection model. The main idea of HeteroNet is that it integrates multiple deep learning models which use heterogeneous dynamic features of malware ***, we implement three heterogeneous deep learning based models to learn various features from three representations, namely API name sequence, API resource graph and API call graph, respectively, each of the representation is built from the run-time trace of malware. Meanwhile, several methods such as attention mechanism and graph neural networks are applied in base models, according to the characteristics of API calls. Finally, an ensemble algorithm is used to integrate the outputs of three base models. We trained and evaluated HeteroNet on a dataset of 28,770 samples. The precision of the model on the testing set reached 98.40%, which is 1.20% higher than the best result of baselines. Moreover, HeteroNet is more robust against concept drift than other baselines. © 2023 IEEE.

关键词： deep learning dynamic analysis ensemble learning malware detection

来源：评论

学校读者我要写书评

暂无评论

An Intelligent Early Warning Support System for Financial Crisis based on Fully Homomorphic Encryption Algorithm

An Intelligent Early Warning Support System for Financial Cr...

引用

distributed systems, computer networks and Cybersecurity (ICDSCNC), international conference on

作者： Fanling Kong College of Finance and Economics Guangdong University of Science &Technology Dongguan China

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

The financial crisis has an important impact on social and economic development, and the existing economic management methods cannot achieve massive data analysis, so on this basis This paper proposes an intelligent early warning support system for financial crisis based on fully homomorphic encryption algorithm to solve the problems of data privacy and security in the traditional early warning system. In this paper, the appropriate CKKS fully homomorphic encryption algorithm is used to implement encryption, decryption and homomorphic operations. The results show that the fully homomorphic encryption algorithm can be simplified, with a simplification rate of 10%, and polynomial adjustment can be realized, which can improve the early warning efficiency of financial crisis to 90%, which is better than the traditional method. Therefore, the financial crisis intelligent early warning system established in this paper can be used and promoted in an efficient and comprehensive manner.

关键词： Economics Data privacy Accuracy Data analysis distributed databases Alarm systems Parallel processing Polynomials Homomorphic encryption Optimization

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 << < 42 43 44 45 46 47 48 49 50 51 > >>

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：