检索结果-内蒙古大学图书馆

Insider Attack Detection Using Deep Belief Neural Network in Cloud Computing

Computer systems Science & engineering 2022年第5期41卷 479-492页

作者： A.S.Anakath R.Kannadasan Niju P.Joseph P.Boominathan G.R.Sreekanth School of Computing E.G.S.Pillay Engineering CollegeNagapattinam611002TamilnaduIndia Department of Software Systems School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014TamilnaduIndia Department of Computer Science CHRIST(Deemed to be University)Bengaluru560029India Department of Information Security School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014TamilnaduIndia Department of Computer Science and Engineering Kongu Engineering CollegeErode638060TamilnaduIndia

Cloud computing is a high network infrastructure where users,owners,third users,authorized users,and customers can access and store their information *** use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing *** cloud is nowadays highly affected by internal threats of the *** applications such as banking,hospital,and business are more likely affected by real user *** intruder is presented as a user and set as a member of the *** becoming an insider in the network,they will try to attack or steal sensitive data during information sharing or *** major issue in today's technological development is identifying the insider threat in the cloud *** data are lost,compromising cloud users is *** and security are not ensured,and then,the usage of the cloud is not *** solutions are available for the external security of the cloud ***,insider or internal threats need to be *** this research work,we focus on a solution for identifying an insider attack using the artificial intelligence *** insider attack is possible by using nodes of weak users’*** will log in using a weak user id,connect to a network,and pretend to be a trusted ***,they can easily attack and hack information as an insider,and identifying them is very *** types of attacks need intelligent solutions.A machine learning approach is widely used for security *** date,the existing lags can classify the attackers *** information hijacking process is very absurd,which motivates young researchers to provide a solution for internal *** our proposed work,we track the attackers using a user interaction behavior pattern and deep learning *** usage of mouse movements and clicks and keystrokes of the real user is stored in a *** deep belief neural

关键词： Cloud computing security insider attack network security privacy user interaction behavior deep belief neural network

来源：评论

学校读者我要写书评

暂无评论

A Comparative Analysis of Multi-agent Simulation Platforms for Energy and Mobility Management 20th

A Comparative Analysis of Multi-agent Simulation Platforms ...

引用

Proceedings of the 20th European Conference on Multi-Agent systems, EUMAS 2023

作者： Ali, Aliyu Tanko Leucker, Martin Schuldei, Andreas Stellbrink, Leonard Sachenbacher, Martin Institute for Software Engineering and Programming Languages University of Lübeck Ratzeburger Allee 160 Lübeck Germany Institute for Multimedia and Interactive Systems University of Lübeck Ratzeburger Allee 160 Lübeck Germany

ISBN: (纸本)9783031432637

Effective energy and mobility management benefits from multi-agent simulations (MAS) to model complex interactions among various agent types. Selecting the optimal MAS platform to implement and simulate these interactions is vital for achieving accurate results, scalability to realistic problem sizes, and efficient computational performance. This paper investigates the energy and mobility domain and identifies key parameters such as the number and complexity of agents, parallel computing power, CPU requirements etc., for developing MAS in the context of this domain. It then presents a comprehensive evaluation of various MAS development platforms. Using a multi-level selection and elimination approach, we narrowed down our evaluation to two final candidates. We then implemented key aspects of our model in both platforms to compare them in terms of practical relevance. Our findings reveal that the *** platform outperforms the Mesa platform in terms of runtime performance, has a smaller memory footprint for large numbers of agents, and offers scalability, making it the most suitable choice for developing MAS for integrated energy and mobility models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Scalability

来源：评论

学校读者我要写书评

暂无评论

Harnessing the Power of AI with Deep Learning: Innovations and Implications

Harnessing the Power of AI with Deep Learning: Innovations a...

引用

2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Upender, Talluri Sathiyamoorthy, C. Udayakumar, K. Kirubakaran, D. Purushothaman, V. Raja, Kiruba Thangam CMR College of Engineering and Technology Department of CSE Medchal Telangana Hyderabad India Department of Commerce Tamil Nadu Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of CSE Tamil Nadu Chennai India R.M.K. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Chennai Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India VIT University Department of Software and Systems Engineering Tamil Nadu Vellore India

ISBN: (纸本)9798331512965

The rapid advancements in artificial intelligence (AI) and deep learning have revolutionized various sectors, enabling unprecedented levels of innovation and efficiency. This paper delves into the transformative impact of deep learning across multiple domains, highlighting key innovations and their broader implications. By examining cutting-edge applications in healthcare, finance, autonomous systems, and natural language processing, the study elucidates how deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), are pushing the boundaries of what's possible. Moreover, the paper explores the integration of deep learning with emerging technologies such as the Internet of Things (IoT), edge computing, and quantum computing, underscoring the synergistic potential of these combinations. The role of deep learning in predictive analytics and personalized solutions is discussed, showcasing its ability to enhance decision-making processes and improve user experiences. Furthermore, the paper discusses the ethical considerations, challenges, and future prospects associated with the widespread adoption of deep learning technologies. The insights provided aim to foster a deeper understanding of how harnessing AI with deep learning can drive progress while addressing critical societal and technological issues. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Continuous American Sign Language Recognition Using Computer Vision And Deep Learning Technologies

Continuous American Sign Language Recognition Using Computer...

引用

2022 IEEE Region 10 Symposium, TENSYMP 2022

作者： Senanayaka, S.A.M.A.S. Perera, R.A.D.B.S. Rankothge, W. Usgalhewa, S.S. Hettihewa, H.D. Abeygunawardhana, P.K.W. Sri Lanka Institute of Information Technology Department of Computer Science & Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (数字)9781665466585

ISBN: (纸本)9781665466585

Sign language is a non-verbal communication method used to communicate between hard of hearing or deaf and ordinary people. Automatic Sign language detection is a complex computer vision problem due to the diversity of modern sign languages and variations in gesture positions, hand and finger form, and body part placements. This research paper aims to conduct a systematic experimental evaluation of computer vision-based approaches for sign language recognition. The present research focuses on mapping non-segmented video streams to glosses to gain insights into sign language recognition. The proposed machine learning model consists of Recurrent Neural Network (RNN) layers such as Long Short-Term Memory (LSTM). The model is implemented using current deep learning frameworks such as Google TensorFlow and Keras API. © 2022 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Deepfake Detection: Emerging Techniques and Evolving Challenges

Deepfake Detection: Emerging Techniques and Evolving Challen...

引用

Annual Information Technology, Electromechanical engineering and Microelectronics Conference (IEMECON)

作者： Krishnaraj Natarajan Abeer Mathur Kshitiz Bhargava Manvendra Singh Moulik Tejpal Department of Database Systems School of Computer Science & Engineering Vellore Institute of Technology Vellore India Department of Software Systems School of Computer Science & Engineering Vellore Institute of Technology Vellore India

ISBN: (数字)9798350387315

ISBN: (纸本)9798350387322

Several newly developed techniques and tools for manipulating images, audio, and videos have been introduced as an outcome of the recent and rapid breakthroughs in AI, machine learning, and deep learning. While most applications for these techniques or tools are in the fields of entertainment and education, some individuals with unlawful intent have also been benefited from them. These individuals use such techniques for various purposes, including the spread of misleading information and unnecessary propaganda, the incitement of political instability, hate and unrest, as well as for purposes of torture and blackmail. These high-quality and convincing manipulated images, audio, or videos are commonly referred to as ‘Deepfakes’.Since then, various solutions to the problems raised by Deepfakes have been proposed in academic studies. This literature review contains relevant publications that offered a variety of approaches to give an updated summary of the research activities in different types of Deepfake attacks, their detection, and countermeasures. It also assesses the effectiveness of the detection capabilities of different techniques with various datasets and algorithms applied in Deepfake detection, while also outlining the various benefits and drawbacks of various methodologies.

关键词： Deep learning Deepfakes Smart contracts Microwave communication Media Forgery Blockchains Internet of Things Systematic literature review Microwave imaging

来源：评论

学校读者我要写书评

暂无评论

Price Estimation of Used Cars Using Machine Learning Algorithms 3rd

Price Estimation of Used Cars Using Machine Learning Algorit...

引用

3rd EAI International Conference on Cognitive Computing and Cyber Physical systems, IC4S 2022

作者： Valarmathi, B. Gupta, N. Srinivasa Santhi, K. Chellatamilan, T. Kavitha, A. Raahil, Armaan Padmavathy, N. Department of Software and Systems Engineering School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Manufacturing Engineering School of Mechanical Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Analytics School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Mathematics School of Advanced Sciences Vellore Institute of Technology Tamil Nadu Vellore India Department of Information Technology School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram India

ISBN: (纸本)9783031289743

In this study, machine learning (ML) techniques are employed to predict used car prices. Several features are used to calculate the price of used cars, but in this paper, we find efficient ways to find the most precise car prices. Despite the fact that there are websites offering this service, they could not employ the most precise prediction system. It is also possible to predict a used car's true market value using a variety of models and techniques. It's important to understand their genuine market value before buying or selling. Both buyers and sellers will be benefitted from these accurate predictions. Support Vector regression, Random Forest regression, and CatBoost regression techniques are used in the proposed system. In the existing method [13], mean absolute error for decision tree regression was 0.6711, which was the least among other algorithms like Linear regression, Lasso regression, Ridge regression, Bayesian Ridge regression, and etc., they used. In the proposed system, mean absolute error (MAE) for Support Vector regression, CatBoost regression and Random Forest regression techniques are 0.1459, 0.1371 and 0.1284 respectively. The prices of second hand/used cars are predicted using the CatBoost regression, Support Vector regression, and Random Forest regression techniques. The accuracy of these algorithms are 86.28%, 85.40% and 87.16%. Among these three algorithms, Random Forest regression gives the least MAE of 0.1317 and the highest accuracy of 87.16%. © 2023, ICST institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

ALU4CED - New Concept for Circular Electronic Design Based on Aluminium

ALU4CED - New Concept for Circular Electronic Design Based o...

引用

Electronics Goes Green 2012+ (EGG)

作者： Marek Koscielski Lutz Stobbe Thomas Mager Tapani Jokinen Adelja Schulz Andrzej Kiernich Grupa Badawcza Technologie Łukasiewicz Research Network - Tele and Radio Research Institute Warsaw Poland Environmental Engineering Fraunhofer Institute for Reliability and Microintegration Berlin Germany Product Engineering Fraunhofer Institute for Mechatronic Systems Design Paderborn Germany

ISBN: (数字)9783000793301

ISBN: (纸本)9798350388220

This paper introduces and presents first results of the joint Polish German research project ALU4CED - aluminium based multifunctional housing for circular electronic devices. ALU4CED has the overarching goal of contributing to the circular economy in the field short living information and communication technology (ICT). It aims to substitute plastic housing by using aluminium which can be recycled which creates a lower carbon footprint over time. This is not a new idea and aluminium housing have been used for a range of products from large remote radio heads in mobile access networks to small devices such as smartphones. However, the novelty of the project lies in the integration of antenna and sensor structures on the outer surface of aluminium housing and creating thermal interface on the inner surface. This paper explains the eco-design concept and novel manufacturing technology that allows to create such multifunctional, resource saving, and easy to recycle aluminium housing.

关键词： Aluminum Thermal sensors Information and communication technology Recycling Manufacturing Plastics Ecodesign

来源：评论

学校读者我要写书评

暂无评论

A novel design approach: increase in storage and transport efficiency for liquid hydrogen by using a dual concept involving a steel-fiber composite tank and thermal sprayed insulating coatings

引用

Frontiers in Energy Research 2024年 12卷

作者： Hauer, Michél Schmidt, Stefan Gericke, Andreas Brätz, Oliver Möhrke, Lukas Biswal, Pratidhwani Stroetmann, Nicco Henkel, Knuth-Michael Department Manufacturing Technologies Thermal Coating Systems Fraunhofer Institute for Large Structures in Production Engineering IGP Rostock Germany Department New Processes and Materials Fiber Composite Technologies Fraunhofer Institute for Large Structures in Production Engineering IGP Rostock Germany Department Manufacturing Technologies Department Lead Fraunhofer Institute for Large Structures in Production Engineering IGP Rostock Germany Department Manufacturing Technologies Thermal Joining Engineering Fraunhofer Institute for Large Structures in Production Engineering IGP Rostock Germany Faculty of Mechanical Engineering and Marine Technologies Chair of Joining Technology University of Rostock Rostock Germany

Wind power-to-gas concepts have a high potential to sustainably cover the increasing demand for hydrogen as an energy carrier and raw material, as it has been shown in the past that there is an enormous potential in energy overproduction, which currently remains unused due to the shutdown of wind turbines. Thus, there is barely experience in maritime production, offshore storage, and transport of large quantities of liquid hydrogen (LH2) due to the developing market. Instead, tank designs refer to heavy standard onshore storage and transport applications with vacuum insulated double wall hulls made from austenitic stainless steel and comparatively high thermal diffusivity and conductivity. This reduces cost effectiveness due to inevitable boil-off and disregards some other requirements such as mechanical and cyclic strength and high corrosion resistance. Hence, new concepts for LH2 tanks are required for addressing these issues. Two innovative technical concepts from space travel and high-temperature applications were adopted, combined and qualified for use in the wind-power-to-gas scenario. The focus was particularly on the high requirements for transport weight, insulation and cryogenic durability. The first concept part consisted of the implementation of FRP (fiber-reinforced plastics)–steel hybrid tanks which have a high potential as a hull for LH2 tanks. However, these hybrid tanks are currently only used in the space sector. Questions still arise regarding interactions with coatings, production, material, temperature resilience and design for commercial use. Thermally sprayed thermal barrier coatings (TBC) in turn show promising potential for surfaces subject to high thermal and mechanical stress. However, the application is currently limited to use at high temperatures and needed to be extended to the cryogenic temperature range. The research on this second part of the concept thus focused on the validation of standard MCrAlY alloys and innovative (partially)

关键词： Corrosion resistance

来源：评论

学校读者我要写书评

暂无评论

Semiautomated 3D Root Segmentation and Evaluation Based on X-Ray CT Imagery

引用

Plant Phenomics 2021年第1期3卷 86-98页

作者： Stefan Gerth Joelle Claußen Anja Eggert Norbert Wörlein Michael Waininger Thomas Wittenberg Norman Uhlmann Development Center X-Ray Technology(EZRT) Fraunhofer Institute for Integrated Systems(IIS)Flugplatzstraße 7590768 FürthGermany Biomedical Engineering Department Fraunhofer Institute for Integrated Systems(IIS)Am Wolfsmantel 331191058 ErlangenGermany

*** X-ray tomography(CTX)is a high-end nondestructive approach for the visual assessment of root architecture in ***,in order to evaluate high-resolution CTX data of root architectures,manual segmentation of the depicted root systems from large-scale volume data is currently necessary,which is both time consuming and error *** duration of such a segmentation is of importance,especially for time-resolved growth analysis,where several instances of a plant need to be segmented and ***,in our application,the contrast between soil and root data varies due to different growth stages and watering situations at the time of ***,the root system itself is expanding in length and in the diameter of individual *** semiautomated and robust root system segmentation from CTX data,we propose the RootForce approach,which is an extension of Frangi’s“multi-scale vesselness”method and integrates a 3D local *** allows a precise delineation of roots with diameters down to severalμm in pots with varying ***,RootForce is not limited to the segmentation of small below-ground organs,but is also able to handle storage roots with a diameter larger than 40 *** CTX volume data of full-grown bean plants as well as time-resolved(3D+time)growth studies of cassava plants,RootForce produces similar(and much faster)results compared to manual segmentation of the regarded root ***,RootForce enables the user to obtain traits not possible to be calculated before,such as total root volume(Vroot),total root length(Lroot),root volume over depth,root growth angles(θmin,θmean,andθmax),root surrounding soil density Dsoil,or form fraction *** proposed RootForce tool can provide a higher efficiency for the semiautomatic high-throughput assessment of the root architectures of different types of plants from large-scale ***,for all datasets

关键词： automated handle Root

来源：评论

学校读者我要写书评

暂无评论

Robust Counting in Overcrowded Scenes Using Batch-Free Normalized Deep ConvNet

引用

Computer systems Science & engineering 2023年第9期46卷 2741-2754页

作者： Sana Zahir Rafi Ullah Khan Mohib Ullah Muhammad Ishaq Naqqash Dilshad Amin Ullah Mi Young Lee Institute of Computer Sciences and Information Technology(ICS/IT) The University of AgriculturePeshawar25130Khyber PakhtunkhwaPakistan Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Collaborative Robotics and Intelligent Systems(CoRIS)Institute Oregon State UniversityORUSA Department of Software Sejong UniversitySeoul05006Korea

The analysis of overcrowded areas is essential for flow monitoring,assembly control,and *** counting’s primary goal is to calculate the population in a given region,which requires real-time analysis of congested scenes for prompt reactionary *** crowd is always unexpected,and the benchmarked available datasets have a lot of variation,which limits the trained models’performance on unseen test *** this paper,we proposed an end-to-end deep neural network that takes an input image and generates a density map of a crowd *** proposed model consists of encoder and decoder networks comprising batch-free normalization layers known as evolving normalization(EvoNorm).This allows our network to be generalized for unseen data because EvoNorm is not using statistics from the training *** decoder network uses dilated 2D convolutional layers to provide large receptive fields and fewer parameters,which enables real-time processing and solves the density drift problem due to its large receptive *** benchmark datasets are used in this study to assess the proposed model,resulting in the conclusion that it outperforms conventional models.

关键词： Artificial intelligence deep learning crowd counting scene understanding

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：