检索结果-内蒙古大学图书馆

3rd International Conference on Advances in Cyber Security, ACeS 2021

作者： Qassim, Qais Saif Jamil, Norziana Mahdi, Mohammed Najah Cob, Zaihisma Che Rahim, Fiza Abd Sidek, Lariyah Mohd University of Technology and Applied Sciences – Ibri Ibri Oman College of Computing and Informatics Universiti Tenaga Nasional Kajang Malaysia School of Computing Universiti Teknologi Malaysia Skudai Malaysia Institute of Energy Infrastructure Universiti Tenaga Nasional Kajang Malaysia

ISBN: (纸本)9789811680588

SCADA systems are commonly used to track and manage utilities in vital national infrastructures including electricity generation and delivery, transportation networks, water supply and manufacturing, and manufacturing facilities. Cyber-attacks that threaten data privacy in SCADA networks, such as unauthorised misuse of sensor or control signals, may have a significant effect on the functioning of sensitive national infrastructure by causing device operators to make incorrect decisions, which could result in disastrous outcomes. Therefore, the cyber-security of SCADA systems has been an active topic of research for the past decades due to the potentially disastrous impact on the environment, public safety, and economy when these systems are breached or compromised. This paper examines the current security posture of SCADA systems from the perspective of data and cybersecurity and to propose recommendations for enhancing protection measures. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

A Framework for Digital Twin Collaboration 24

A Framework for Digital Twin Collaboration

引用

Proceedings of the Winter Simulation Conference

作者： Zhengchang Hua Karim Djemame Nikos Tziritas Georgios Theodoropoulos Dept. of Computer Science and Eng. Southern University of Science and Technology (SUSTech) Shenzhen CHINA and School of Computing University of Leeds Leeds UK School of Computing University of Leeds Leeds UK Dept. of Informatics and Telecommunications University of Thessaly Lamia GREECE Research Institute of Trustworthy Autonomous Systems (RITAS) SUSTech Shenzhen CHINA and Dept. of Computer Science and Eng. Southern University of Science and Technology (SUSTech) Shenzhen CHINA

ISBN: (纸本)9798331534202

Digital Twins (DTs) have emerged as a powerful tool for modeling Large Complex Systems (LCSs). Their strength lies in the detailed virtual models that enable accurate predictions, presenting challenges in traditionally centralized approaches due to the immense scale and decentralized ownership of LCSs. This paper proposes a framework that leverages the prevalence of individual DTs within LCSs. By facilitating the exchange of decisions and predictions, this framework fosters collaboration among autonomous DTs, enhancing performance. Additionally, a trust-based mechanism is introduced to improve system robustness against poor decision-making within the collaborative network. The framework's effectiveness is demonstrated in a virtual power plant (VPP) scenario. The evaluation results confirm the system's objectives across various test cases and show scalability for large deployments.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improving Model Performance for Air Temperature and Precipitation by Assimilating Global Leaf Area Index Products

Improving Model Performance for Air Temperature and Precipit...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiaolu Ling Yong Xue School of Environment and Spatial Informatics China University of Mining and Technology Xuzhou China Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and Utilization China University of Mining and Technology Xuzhou China School of Electronics Computing and Mathematics College of Engineering and Technology University of Derby Derby UK

Vegetation parameter, especially the leaf area index (LAI), is a key variable that take part in the land-atmosphere interaction. Many studies have found that by updating LAI in land surface models can improve the simulation ability for land surface variables. This study used the coupled Community Land Model with explicit carbon and nitrogen components (CLM4CN) and Community Atmosphere Model (CAM) as well as Data Assimilation Research Testbed (DART) to update assimilated LAI, to improve the simulation ability for air temperature and precipitation. The Global Land Surface Data Assimilation System (GLDAS) reanalysis data were used to estimate the coupled CLM4CN/CAM/DART performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Influence of LAI Change on Regional Climate Under Land-Atmosphere Coupling

Influence of LAI Change on Regional Climate Under Land-Atmos...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Zeyu Tang Xiaolu Ling Yong Xue School of Environment and Spatial Informatics China University of Mining and Technology Xuzhou China Jiangsu Key Laboratory of Coal-based Greenhouse Gas Control and Utilization China University of Mining and Technology Xuzhou China School of Electronics Computing and Mathematics College of Engineering and Technology University of Derby Derby UK

As an important parameter to characterize land surface vegetation, leaf area index (LAI) is not only an important vegetation biophysical parameter that affects surface radiation transfer and material and energy balance, but also an important parameter to connect micro biogeochemical processes such as photosynthesis and respiration of vegetation. Because of the strong inhomogeneity of the lower land surface, correct description of the canopy structure as well as canopy physical and biogeochemical processes is the basis and prerequisite for the correct description of surface radiation characteristics and land-air interaction. In this paper, based on the Community Land Model (CLM4) and Data Assimilation Research Testbed (DART) developed by the National Center for Atmospheric Research (NCAR), the Global LAnd Surface Satellite (GLASS) LAI data are assimilated into the carbon and nitrogen component of CLM4 (CLM4-CN), and the impact of LAI change on climate change on a regional scale is further analyzed in the case of land-atmosphere coupling.

关键词：

来源：评论

学校读者我要写书评

暂无评论

xIDS-EnsembleGuard: An Explainable Ensemble Learning-based Intrusion Detection System 23

xIDS-EnsembleGuard: An Explainable Ensemble Learning-based I...

引用

23rd IEEE International Conference on Trust, Security and Privacy in computing and Communications, TrustCom 2024

作者： Adil, Muhammad Jan, Mian Ahmad Bin Hakim, Safayat Song, Houbing Herbert Jin, Zhanpeng University at Buffalo Deptartment of Computer Science Buffalo United States University of Sharjah College of Computing and Informatics Sharjah United Arab Emirates University of Maryland School of Information Systems Baltimore County United States South China University of Technology Guangdong China University at Buffalo School of Future Technology Buffalo United States

In this paper, we focus on addressing the challenges of detecting malicious attacks in networks by designing an advanced Explainable Intrusion Detection System (xIDS). The existing machine learning and deep learning approaches have invisible limitations, such as potential biases in predictions, a lack of interpretability, and the risk of overfitting to training data. These issues can create doubt about their usefulness, and transparency, and decrease the trust of involved stakeholders. To overcome these challenges, we propose an ensemble learning technique called the "EnsembleGuard". This approach uses the predicted outputs of multiple models, including tree-based (LightGBM, GBM, Bagging, XGBoost, CatBoost) and deep learning models such as neural network (LSTM (long short-term memory networks) and GRU (gated recurrent unit), to maintain a balance and achieve trustworthy results. Our work is unique because it combines both tree-based and deep learning models to design an interpretable and explainable meta-model through model distillation. By considering the predictions of all individual models, our neta-model effectively addresses key challenges, and ensures both explainable and reliable results. We evaluate our model using well-known datasets, including UNSW-NB15, NSL-KDD, and CIC-IDS-2017, to assess its reliability against various types of attacks. During analysis, we found that our model outperforms both tree-based models and other comparative approaches when it comes to different kinds of attack scenarios. © 2024 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Structural Balance in Real-World Social Networks: Incorporating Direction and Transitivity in Measuring Partial Balance

arXiv

引用

arXiv 2024年

作者： Rezapour, Rezvaneh Dinh, Ly Jiang, Lan Diesner, Jana College of Computing and Informatics Drexel University PhiladelphiaPA United States School of Information University of South Florida TampaFL United States School of Information Sciences University of Illinois at Urbana-Champaign ChampaignIL United States School of Social Sciences and Technology Technical University of Munich Munich Germany

Structural balance theory predicts that triads in networks gravitate towards stable configurations. The theory has been verified for undirected graphs. Since real-world networks are often directed, we introduce a novel method for considering both transitivity and sign consistency for evaluating partial balance in signed digraphs. We test our approach on graphs constructed by using different methods for identifying edge signs: natural language processing to infer signs from underlying text data, and self-reported survey data. Our results show that for various social contexts and edge sign detection methods, partial balance of these digraphs are moderately high, ranging from 61% to 96%. Our approach not only enhances the theoretical framework of structural balance but also provides practical insights into the stability of social networks, enabling a deeper understanding of interpersonal and group dynamics across different communication platforms. © 2024, CC BY.

关键词： Directed graphs

来源：评论

学校读者我要写书评

暂无评论

Quantifying the Benefits of Implementing Big Data Analytics on Consumers’ Online Purchase Intentions in e-Commerce

Quantifying the Benefits of Implementing Big Data Analytics ...

引用

2024 IEEE International Conference on computing, ICOCO 2024

作者： Wei, Justin Ang Kang Mansor, Mahayaudin M. Derasit, Zuraidah Bakar, Mohd Aftar Abu Ul-Saufie, Ahmad Zia Hamzah, Firdaus Mohamad Faculty of Business Economics and Accounting HELP University Kuala Lumpur Malaysia School of Mathematical Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Malaysia Institute for Big Data Analytics and Artificial Intelligence Universiti Teknologi MARA Selangor Shah Alam Malaysia Department of Mathematical Sciences Faculty of Science & Technology Universiti Kebangsaan Malaysia Malaysia Centre for Defence Foundation Studies Universiti Pertahanan Nasional Malaysia Kuala Lumpur Malaysia

ISBN: (纸本)9798331530303

The digital revolution has reshaped the global economy, especially e-commerce. Innovative technologies such as big data analytics, artificial intelligence, and cloud computing drive this transformation, enabling companies to make informed business decisions and influence consumers’ online purchasing behaviour. This study explores empirical evidence for the benefits of using big data analytics (BDA) to influence consumers’ online purchasing decisions in e-commerce. Primary data was collected via an online survey targeting 300 customers with online shopping experience on platforms that have adopted the digital technologies of BDA. Statistical methods used in this study included questionnaire design, reliability test, descriptive analysis, and multiple regression modelling and diagnostics. The findings indicate that the benefits of implementing BDA in e-commerce for information search, recommendation systems, consumer services, dynamic pricing, security and fraud detection are strongly associated with consumers’ online purchasing intentions. The study underscores the importance of businesses leveraging BDA, as the benefits significantly and positively impact consumers’ purchasing intentions in e-commerce while addressing security and fraud detection concerns that undermine its advantage. Nevertheless, we encourage all companies to leverage BDA implementation in their digital marketplace, which ultimately contributes to achieving e-commerce goals, such as increased market reach, cost reduction, and revenue growth. ©2024 IEEE.

关键词： Marketplaces

来源：评论

学校读者我要写书评

暂无评论

A Comparison Study on Generative Adversarial Networks (GANs) for Satellite Image Upscaling

A Comparison Study on Generative Adversarial Networks (GANs)...

引用

IEEE Conference on Systems, Process & Control (ICSPC)

作者： Brandon Kah Wei Li Muhammed Basheer Jasser Bayan Issa Samuel-Soma M. Ajibade Hui Na Chua Richard T.K. Wong Muzaffar Hamzah Department of Computing and Information Systems School of Engineering and Technology Sunway University No. 5 Jalan Universiti Bandar Sunway Selangor Darul Ehsan Malaysia Research Centre For Human-Machine Collaboration (HUMAC)School of Engineering and Technology Sunway University No. 5 Jalan Universiti Bandar Sunway Selangor Darul Ehsan Malaysia Faculty of Informatics Engineering University of Aleppo Syria Department of Computer Engineering Istanbul Ticaret University Istanbul Turkiye Faculty of Computing and Informatics Universiti Malaysia Sabah Kota Kinabalu Sabah Malaysia

ISBN: (数字)9798350391398

ISBN: (纸本)9798350391404

Satellite images that are publicly available on the internet such as Google Maps are mostly low-quality and blurry which is not very useful for research or decision-making due to the lack of details. Recently image upscaling has been increasing in popularity to address several real-world problems where one approach is using Convolutional Neural Networks (CNNs). However, CNNs have difficulty in restoring fine details and this has led to the use of Generative adversarial networks (GANs) for image scaling. In this paper, three GAN models are trained which are Enhanced Super-Resolution Generative Adversarial Networks (Real-ESRGAN), Image Restoration Using Swin Transformer (SwinIR-Medium), and Dual Aggregation Transformer (DAT-2). The models are evaluated with well-known image metrics to determine each model’s effectiveness in upscaling low-resolution satellite images. The results show that all models can reconstruct the image to some degree where the best out of the three is DAT-2. Further fine-tuning of the best model by changing the loss functions has shown improvements in structural integrity for the upscaled image.

关键词： Training Photography Measurement Web services Generative adversarial networks Transformers Satellite images Image restoration Particle swarm optimization Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

SYN Flood Attack Detection and Prevention Technique (SFaDMT) in Distributed Environment

SYN Flood Attack Detection and Prevention Technique (SFaDMT)...

引用

International Conference on Emerging Trends in Networks and Computer Communications (ETNCC)

作者： Halawati Abd Jalil Fufan Basheer Riskhan Khalid Hussain Husin Bin Jazri Samah H. Alajmani Komal Sharma School of Computing and Informatics Albukhary International University Alor Setar Malaysia School of Computer Science Taylor's University Subang Jaya Malaysia Department of Information Technology Taif University Taif Saudi Arabia Division of Research and Development Lovely Professional University Phagwara KKR and KSR institute of technology and sciences Guntur Andhra Pradesh

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

In the modern digital landscape, cyber-attacks have become highly advanced and difficult to detect, especially in distributed systems. These Denial of Service (DoS) or Distributed Denial of Service (DDoS) attacks lead to resource unavailability for legitimate users, causing financial losses for organizations. To counter these threats, researchers have proposed efficient mitigation techniques. According to Kaspersky's Q3 report, SYN Flood is the most prevalent type of D DoS attack, increasing from 76% to 81% compared to the Q2 report. DDoS attacks can be executed directly or indirectly. In a direct attack, control traffic is sent straight from the attackers to the zombies to target the victim host. Conversely, in an indirect DDoS attack, control traffic is sent indirectly to reflectors by zombies to compromise the target host. Reflectors are uncompromised systems that only respond to requests. To mitigate such attacks, traffic shaping and Pushback techniques are employed. Our research introduces an adaptive heuristic-based method called SYN Flood Attack Detection and Mitigation Technique (SFaDMT) to detect DDoS SYN flood attacks. This study proposes an efficient technique for detecting and blocking SYN attacks. The SFaDMT technique is based on a decision support mechanism. The proposed model is simulated and analyzed in the OMNET simulator, and a comparison is made with the latest technique. The results demonstrate an improvement in detection with the proposed solution.

关键词： Filters Prevention and mitigation Organizations Traffic control Denial-of-service attack Market research Floods Engines Cyberattack Payloads

来源：评论

学校读者我要写书评

暂无评论

Asynchronous Federated Clustering with Unknown Number of Clusters

arXiv

引用

arXiv 2024年

作者： Zhang, Yunfan Zhang, Yiqun Lu, Yang Li, Mengke Chen, Xi Cheung, Yiu-Ming School of Computer Science and Technology Guangdong University of Technology Guangzhou China Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University Xiamen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Computer Science Hong Kong Baptist University Hong Kong

Federated Clustering (FC) is crucial to mining knowledge from unlabeled non-Independent Identically Distributed (non-IID) data provided by multiple clients while preserving their privacy. Most existing attempts learn cluster distributions at local clients, and then securely pass the desensitized information to the server for aggregation. However, some tricky but common FC problems are still relatively unexplored, including the heterogeneity in terms of clients’ communication capacity and the unknown number of proper clusters k∗. To further bridge the gap between FC and real application scenarios, this paper first shows that the clients’ communication asynchrony and unknown k∗ are complex coupling problems, and then proposes an Asynchronous Federated Cluster Learning (AFCL) method accordingly. It spreads the excessive number of seed points to the clients as a learning medium and coordinates them across the clients to form a consensus. To alleviate the distribution imbalance cumulated due to the unforeseen asynchronous uploading from the heterogeneous clients, we also design a balancing mechanism for seeds updating. As a result, the seeds gradually adapt to each other to reveal a proper number of clusters. Extensive experiments demonstrate the efficacy of AFCL. Copyright © 2024, The Authors. All rights reserved.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

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：

请选择收藏分类：

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

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：