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
84 篇 期刊文献

馆藏范围

5,374 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,879 篇 工学
- 2,570 篇 计算机科学与技术...
- 1,720 篇 软件工程
- 968 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
355 篇 wireless sensor ...
308 篇 computer network...
254 篇 protocols
249 篇 computer archite...
219 篇 intrusion detect...
213 篇 authentication
210 篇 computer communi...
201 篇 ip networks
193 篇 computer crime
172 篇 servers
166 篇 computer securit...
160 篇 network security
158 篇 information secu...
155 篇 internet of thin...
150 篇 distributed comp...
147 篇 computer science
146 篇 cryptography
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

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

5,022 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 5374 条记录，以下是1081-1090 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：

MnemoSys: A Conditional Probability Estimation Protocol for Blockchain Audited Reputation Management

MnemoSys: A Conditional Probability Estimation Protocol for ...

引用

IEEE international conference on Trust, Privacy and security in Intelligent systems and Applications (TPS-ISA)

作者： Daniel Rouhana Peyton Lundquist Tim Andersen Gaby G. Dagher Department of Computer Science Washington State University Department of Computer Science Boise State University

Reputation systems have been one method of solving the unique challenges that face distributed networks of independent operators. Fundamentally, historical performance must be considered in a way that attempts to predict future behav-ior, optimize present functionality, and provide some measure of immutable recording. In this paper, a three-part system, MnemoSys, is proposed to solve this diverse set of problems. First, historical performance is dynamically weighted and scored using geometrically expanding time windows. Second, a quorum is abstracted as a restricted Boltzmann machine to produce a conditional probability estimate of log-normal likelihood of good-faith behavior. Third, all rewards and punishments are recorded on an immutable, decentralized ledger. Our experimentation shows that when applied iteratively to an entire network, consistently under-performing nodes are removed, network stability is maintained even with high percentages of simulated error, and global network parameters are optimized in the long-term.

关键词： Protocols Error analysis Estimation Probabilistic logic Stability analysis Behavioral sciences Recording

来源：评论

学校读者我要写书评

暂无评论

Synthesis of Adversarial DDoS Attacks Using Wasserstein Generative Adversarial networks with Gradient Penalty

Synthesis of Adversarial DDoS Attacks Using Wasserstein Gene...

引用

6th international conference on Computational Intelligence and Applications, ICCIA 2021

作者： Shieh, Chin-Shiuh Nguyen, Thanh-Tuan Lin, Wan-Wei Huang, Yong-Lin Horng, Mong-Fong Lee, Tsair-Fwu Miu, Denis National Kaohsiung University of Science and Technology Department of Electronic Engineering Taiwan Genie Networks Ltd Taiwan

ISBN: (纸本)9781665439336

DDoS (distributed Denial of Service) has become a pressing and challenging threat to the security and integrity of computer networks and information systems. The detection of DDoS attacks is essential before any mitigation approaches can be taken. AI (Artificial Intelligence) and ML (Machine Learning) have been applied to the detection of DDoS attacks with satisfactory achievement. However, new types of attacks emerge as the technology for DDoS attacks keep evolving. This study investigates the impact of a new sort of DDoS attack - adversarial DDoS attack. We synthesize attacking traffic using Wasserstein Generative Adversarial networks with Gradient Penalty (GPWGAN). Experiment results reveal that the synthesized traffic can penetrate the systems, including Random Forest, k-Nearest Neighbor, and Multi-Layer Perceptron, without being detected. This observation is an alarming and pessimistic wake-up call implying the urgent need for countermeasures to adversarial DDoS attacks. © 2021 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

An Autoencoder-Based Approach for DDoS Attack Detection Using Semi-Supervised Learning

An Autoencoder-Based Approach for DDoS Attack Detection Usin...

引用

Next-Generation Computing, IoT and Machine Learning (NCIM), international conference on

作者： Tamanna Fardusy Sayma Afrin Ifrat Jahan Sraboni Uttam Kumar Dey Department of Computer Science and Engineering Uttara University Dhaka Bangladesh

A distributed Denial of Service (DDoS) attack is a malicious cyber-attack strategy that seeks to disrupt normal traffic to a specific server by overwhelming it with an excessive amount of requests or data. In recent years, there has been a persistent increase in the use of DDoS attacks to exploit Internet networks. Although advanced intrusion detection and protection systems have been developed, network security remains a difficult problem and requires the development of effective defense mechanisms to detect these threats. Most of the current approaches are based on supervised learning which requires large and well-balanced datasets. Still, they struggle to identify new types of attacks. To address these issues, we propose a semi-supervised DDoS detection model using Autoencoder (AE) and Support Vector Machine (SVM). We compared our proposed approach with various supervised and semi-supervised models on the CICDDoS2019 dataset. Our proposed model outperformed the other models by achieving an accuracy of 99.57% and over 99% precision, recall, and F1 score.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Efficiency-enhanced Blockchain-based Client Selection in Heterogeneous Federated Learning

Efficiency-enhanced Blockchain-based Client Selection in Het...

引用

IEEE international conference on Blockchain (Blockchain)

作者： Zhiqi Lei Keke Gai Jing Yu Shuo Wang Liehuang Zhu Kim-Kwang Raymond Choo School of Computer Science and Technology Beijing Institute of Technology Beijing China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing Zhejiang China School of Cyberspace Science and Technology Beijing Institute of Technology Beijing China Chinese Academy of Sciences Institute of Information Engineering Beijing China Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio TX USA

In Federated Learning (FL), blockchain has been extensively used to achieve distributed and tamper-resistant data processing. However, typical Blockchain-based Federated Learning (BFL) rarely considers clients’ resource and computing limits. High-capacity clients may be sacrificed when all clients train on the same neural network. This paper proposes a Blockchain-based Heterogeneous Federated Learning (BlocFL) model to address the challenges above. BlocFL replaces the central server with a consortium blockchain, and several neural networks are employed for local training. Considering the challenges in resource allocation in BFL, especially in heterogeneous networks, we propose a consortium blockchain-based heterogeneous federated learning client selection method. The proposed method optimizes the choice of client nodes under the limits of computational resources. Experiment results demonstrate that our method can allocate appropriate neural network models to each client and effectively improve the efficiency of local training in HFL. It also can achieve a comparable level of accuracy to the baseline approach with similar training parameters.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Piecing Together the Jigsaw Puzzle of Transactions on Heterogeneous Blockchain networks 25

Piecing Together the Jigsaw Puzzle of Transactions on Hetero...

引用

Abstracts of the 2025 ACM SIGMETRICS international conference on Measurement and Modeling of computer systems

作者： Xiaohui Hu Hang Feng Pengcheng Xia Gareth Tyson Lei Wu Yajin Zhou Haoyu Wang Huazhong University of Science and Technology Wuhan Zhejiang China Zhejiang University Hangzhou Zhejiang China Huazhong University of Science and Technology Wuhan Hubei China Hong Kong University of Science and Technology (GZ) Guangzhou Guangdong China

ISBN: (纸本)9798400715938

The Web3 ecosystem is increasingly evolving to include multiple chains, with decentralized applications (dApps) distributed across different blockchains. This has driven the need for cross-chain bridges to enable blockchain interoperability. However, this opens up novel attack surface, and media outlets have reported serious attacks related to cross-chain bridges. Nevertheless, few prior works have studied cross-chain bridges and their related transactions, especially from a security perspective. To fill the void, this paper presents the first comprehensive analysis of cross-chain transactions. We first build a cross-chain transaction dataset based on semantic analysis of popular cross-chain bridges, covering 13 decentralized bridges and 7 representative blockchains, with over 80 million transactions in total. Based on this comprehensive dataset, we study the landscape of cross-chain transactions from several angles, including token usage, user profile and the purposes of transactions. We further observe that cross-chain bridges can be abused for malicious/aggressive purposes. Thus we design an automated detector and deploy it in-the-wild to flag misbehaviors from millions of cross-chain transactions. We identify hundreds of abnormal transactions related to exploits and arbitrages, etc. Our research underscores the importance of the cross-chain ecosystem, and offers an effective detector for pinpointing security threats.

关键词： blockchain

来源：评论

学校读者我要写书评

暂无评论

Medchain: Securing Electronic Medical Records with a Peer to Peer networks and distributed File System 1

引用

3rd international conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2020

作者： Gururaj, H.L. Goutham, B. Janhavi, V. Suhas, K.C. Manu, M.N. Vidyavardhaka College of Engineering Mysuru India Channabasaveshwara Institute of Technology Tumkur India SJB Institute of Technology Bengaluru India

ISBN: (数字)9789811614804

ISBN: (纸本)9789811614798

Though the advances in technology have changed every aspect of our lives, it has barely budged the way we think about our medical records being stored across various platforms. This electronic document talks about the problem that has always existed in the medical field but has failed to be solved;Privacy in the current electronic medical record systems. This paper discusses the failure of traditional medical record systems in terms of security and sustenance to ease of use and provides a possible solution to use today’s technology to address the disadvantages. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Radio frequency identification (RFID)

来源：评论

学校读者我要写书评

暂无评论

Impact of Aggregation Function Randomization against Model Poisoning in Federated Learning

Impact of Aggregation Function Randomization against Model P...

引用

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

作者： Seyedsina Nabavirazavi Rahim Taheri Mohammad Shojafar Sundararaja Sitharama Iyengar School of Computing and Information Sciences Florida International University USA Faculty of Technology School of Computing University of Portsmouth UK 5G/6G Innovation Centre (5G/6GIC) Institute for Communication Systems University of Surrey UK

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Federated learning has gained significant attention as a privacy-preserving approach for training machine learning models across decentralized devices. However, this distributed learning paradigm is susceptible to adversarial attacks, particularly model poisoning attacks, where adversaries inject malicious model updates to compromise the integrity of the global model. In this paper, we investigate the impact of randomness on model poisoning attacks in federated networks, where the server employs two aggregation rules, Krum and Trimmed Mean, randomly in each federated round. We present three distinct adversaries: one targeting Krum throughout the entire learning process, another targeting Trimmed Mean entirely, and a third adversary employing a randomized strategy between Krum and Trimmed Mean for each round. Our objective is to evaluate their performance in reducing the overall accuracy of the federated network. We propose novel techniques to craft poisoned models and explore the efficacy of these attacks by exploiting the aggregation rules. We evaluated our proposed methods on Fashion-MNIST dataset. The experiments reveal the robustness of the federated network against the proposed adversarial scenarios, contributing to a better understanding of the vulnerabilities and defenses in federated learning systems.

关键词： Training Privacy computer aided instruction Federated learning Distance learning Computational modeling Robustness

来源：评论

学校读者我要写书评

暂无评论

Safety in distributed Sensor networks: A Literature Review 5

Safety in Distributed Sensor Networks: A Literature Review

引用

5th international conference on Internet of Things, Big Data and security (IoTBDS)

作者： Altenburg, Tobias Bosse, Sascha Turowski, Klaus Otto von Guericke Univ Fac Comp Sci Very Large Business Applicat Lab Magdeburg Germany

ISBN: (纸本)9789897584268

The connectivity megatrend dominates the current social change. The number of networked devices and the resulting amount of data is constantly increasing worldwide. For this reason, the dependability of computer systems is becoming increasingly relevant. Especially in the context of civil infrastructures, the constant availability of computer systems is of great importance. This paper provides a structured overview of the current literary status of safety in distributed sensor networks. Most approaches from the literature focus on the design phase. By the following connection with the existing dependability theory, the potential for the optimization of dependability could be proven.

关键词： Dependability Sensor Network Internet of Things Fault Tolerance Fault Prevention

来源：评论

学校读者我要写书评

暂无评论

Analysis of BayesNet Classifier for DDoS Detection in Vehicular networks

Analysis of BayesNet Classifier for DDoS Detection in Vehicu...

引用

Augmented Intelligence and Sustainable systems (ICAISS), international conference on

作者： Amandeep Verma Rahul Saha School of Computer Science and Engineering Lovely Professional University India

ISBN: (纸本)9781665489638

In vehicular networks, distributed Denial of Service (DDoS), an extension of Denial of Service (DoS) attacks, disrupt the normal vehicular network services. Existing DDoS detection systems in vehicular networks use a variety of Machine Learning (ML) methods. These techniques claim to be relevant and successful in attack detection in vehicular networks. The ML-based solutions use DDoS dynamics like adaptive traffic, heterogeneity, and packet features etc. As a result, a question arises whether these ML-based techniques are capable of handling novel security threats. In this paper, we use BayesNet technique on different datasets to test its performance and analyse the results to validate its usage for protecting against novel network security threats. BayesNet helps in decision making by improving data management and analysis. We use two datasets: simulation-based dataset and CIC-DDoS-2019 dataset. The CIC-DDoS-2019 dataset has 12 subsets and we use SYN, UDPLag and Portmap data subset. These datasets contain three types of DDoS attacks, i.e., SYN-flood attack, UDPLag attack, and Portmap attack. We test BayesNet to see the performance of the algorithm in detecting the mentioned forms of DDoS. We consider the parameters of accuracy, True Positive Rate (TPR), and False Positive Rate (FPR) for performance evaluation. In all the results, we observe that accuracy is always higher than 90%. TPR is very high, i.e. weighted TPR is 0.99 and wighted FPR of all tests is 0.076 that is quiet low. All these results prove that BayesNet ML technique is capable of detecting DDoS attack forms significantly.

关键词： Performance evaluation Adaptive systems Decision making Machine learning Network security Denial-of-service attack computer crime

来源：评论

学校读者我要写书评

暂无评论

Macroscopic Insights of IoT Botnet Dynamics Via AS-level Tolerance Assessment

Macroscopic Insights of IoT Botnet Dynamics Via AS-level Tol...

引用

IEEE international conference on Communications (ICC)

作者： Hatem A. Almazarqi Mathew Woodyard Angelos K. Mamerides Department of Information Technology Faculty of Computing and Information Technology in Rabigh King Abdulaziz University Rabigh Saudi Arabia School of Computing Science University of Glasgow Glasgow Scotland UK Okta Inc. San Francisco CA USA Dept. of Electrical & Computer Engineering & KIOS CoE University of Cyprus Nicosia Cyprus

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

The ubiquitous integration of the IoT in current sociotechnical systems alongside the manufacturing of IoT devices and IoT-enabled services equipped with minimal security, has profoundly altered the cyber-threat landscape. Consequently, the overwhelming majority of cyberattacks utilise compromised IoT devices as a vessel for initiating large scale volumetric (e.g., DDoS) or stealthy Advanced Persistent Threats (APTs) such as ransomware through well orchestrated IoT botnets. Due to the constantly evolving nature of these botnets and their diverse structural characteristics, tracking their activities poses considerable challenges since malicious actors and botnet owners often adopt new strategies to evade detection and expand their botnet network. Evidently, Autonomous systems (ASes) and their implied organisational and regulatory properties play a crucial role in botnet propagation. In this paper, we present a novel and extensive macroscopic measurement study quantifying AS-level tolerance in the context of IoT botnet behavioral dynamics across the global IPv4 address space. In order to verify and justify our hypotheses in terms of AS-level tolerance we conduct a longitudinal analysis over 3.8M malicious events triggered by IoT botnets across over 8K ASes using measurements gathered through globally distributed honeypots, IP blacklists and Internet regional registries for a three year period. We argue that the findings in the herein work can greatly benefit a range of stakeholders designing, operating, and managing current defense mechanisms as well as contributing significantly towards the evolution of next generation cyber defense mechanisms.

关键词： Sociotechnical systems Botnet Routing Vectors Blocklists Internet of Things IP networks

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 << < 105 106 107 108 109 110 111 112 113 114 > >>

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：