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检索条件"任意字段=3rd International Conference on Distributed Computing and Internet Technology, ICDCIT 2006"

共 396 条记录，以下是21-30 订阅

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Sliced Bidirectional Gated Recurrent Unit with Sparrow Search Optimizer for Detecting the Attacks in IoT Environment 3

Sliced Bidirectional Gated Recurrent Unit with Sparrow Searc...

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3rd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Gondkar, Sureka R. Siva Balan, R.V. Kavitha, S. Gondkar, Raju Ramakrishna Bms Institute Of Technology And Management Department Of Electronic And Communication Engineering Bangalore India Department Of Computer Science Bangalore India Nitte Meenakshi Institute Of Technology Department Of Mca Bangalore India

ISBN: (纸本)9798350318609

In an era characterized by pervasive interconnectivity facilitated by the widespread adoption of internet of Things (IoT) devices across diverse domains, novel cybersecurity challenges have emerged, underscoring the imperative for robust intrusion detection systems. Conventional security frameworks, constrained by their closed-system architecture, struggle to adapt to the dynamic threat landscape marked by the continual emergence of unprecedented attacks. This paper presents a methodology aimed at mitigating the open set recognition (OSR) challenge within IoT-specific Network Intrusion Detection Schemes (NIDS). Leveraging image-based representations of data, our approach focuses on extracting geographical traffic patterns. We observe that the Recurrent Neural Network exhibits suboptimal classification accuracy and lacks parallelizability for attack analysis tasks. Our investigation concludes that the Sparrow Search Optimization Algorithm (SSOA) serves as a foundation for constructing an effective assault classification model. This research contributes significantly to the field of network security by emphasizing the importance and ramifications of meticulous hyperparameter tuning. It represents a critical stride toward developing IDSs capable of effectively navigating the evolving cyber threat landscape. In the experimental analysis of proposed model reached the accuracy and 0.963% respectively. © 2024 IEEE.

关键词： internet of things

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Transformer Fault Diagnosis Using Deep Boltzmann Machine and Multiclass Relevance Vector Machines 3

Transformer Fault Diagnosis Using Deep Boltzmann Machine and...

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3rd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Sudhakar, A.V.V. Satish, E.G. Shravani, B. Sharma, Rakesh Al-Jawahry, Hassan M. Sr University Department Of Electrical And Electronics Engineering Warangal India Nitte Meenakshi Institute Of Technology Dept.of Cse Bengaluru India Department Of Eee Ananthapuramu India Srinivas Institute Of Technology Department Of Cse Valachil Mangalore India College Of Technical Engineering The Islamic University Department Of Computers Techniques Engineering Najaf Iraq

ISBN: (纸本)9798350318609

Transformers are crucial to electric power systems, yet it can be challenging to accurately diagnose their problems. The research presents a novel method for transformer defect diagnostics that combines ensemble machine learning (EML) with an internet of Things (IoT) based monitoring model. First, the data measurement subsystem measures the transformer vibration signals, and data reception transmits those signals to remote server. At that time, an EML made up of Multiclass Relevance Vector Machines (MRVMs) and Deep Boltzmann Machines (DBM) functions are suggested. A unique combination strategy and conventional monitoring techniques like vibro-acoustic frequency and short-circuit impedance are used to guarantee the EML's efficiency. The suggested EML readily addresses the insufficient feature extraction information from separate deep learning methods, and the multiclass RVM classification technique clearly outperforms other widely used classifiers. The less power, long-distance watching, and high reliable utilization based on IoT is advantageous for long-term collection and transmission of signals. The study of the results makes it evident that the suggested DBM-MRVM outperformed other models, achieving a greater accuracy of 99.38%. © 2024 IEEE.

关键词： internet of things

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IoT-Based Smart Waste Management System with Level Indicators for Effective Garbage Waste Segregation 3

IoT-Based Smart Waste Management System with Level Indicator...

引用

3rd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Varghese, Mary P. Anooja, V.S. Akhila, R. Krishnakumar, M. Xavier, Arun Vidya Academy Of Science & Technology Department Of Electrical & Electronics Engineering Thrissur India

ISBN: (纸本)9798350318609

The rapid growth in urbanization and population has increased the generation of municipal solid garbage, providing significant challenges to waste management systems. Hence, to solve the issues in waste management, it suggested internet of Things (IoT) smart-based Smart Waste Management (SWM) with level indications. This system combines IoT technologies to improve the efficiency and sustainability of the garbage disposal process. The suggested SWM system includes sensor-equipped garbage bins that can monitor and transmit accurate information on their fill levels. Sensor-equipped garbage bins optimize waste disposal by providing real-time data, enhancing efficiency and providing timely predictions in trash management. Furthermore, the use of smart garbage bins helps the separation of various types of waste, increasing eco-friendly behaviors and helping recycling activities. The level indicators not only improve efficiency but also help to reduce environmental effects by lowering overflowing bins and eliminating waste. As a result, this research makes use of the architecture, functionality, and potential benefits of the IoT based SWM system, highlighting its role in supporting responsible waste management practices, resource conservation, and the development of urban areas. © 2024 IEEE.

关键词： internet of things

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A Blockchain Architecture for Secure Decentralized System and computing 3

A Blockchain Architecture for Secure Decentralized System an...

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3rd international conference on Power Electronics and IoT Applications in Renewable Energy and its Control, PARC 2024

作者： Avasthi, Sandhya Jain, Khushboo Prakash, Ayushi Sanwal, Tanushree ABES Engineering College Department of CSE UP Ghaziabad India School of Computer Science UPES UK Dehradun India AKGEC Engineering College Department of CSE Ghaziabad India KIET School of Management KIET Group of Institutions Delhi-NCR Ghaziabad India

ISBN: (纸本)9798350309409

Recent growth in internet infrastructure has increased demands for internet technology and so there is a need for a secure decentralized system that is combined with secure and transparent infrastructure. Blockchain technology can store information in a distributed manner securely. Blockchain technology has expanded significantly over the past few years, with new applications and use cases being discovered and developed every day. The decentralized nature of blockchain, combined with its secure and transparent infrastructure, has made it a highly sought-after solution for various industries, including finance, healthcare, supply chain management, and government services. The expansion of blockchain technology is a result of its increasing adoption and integration into various sectors such as finance, healthcare, supply chain management, and more. One of the key drivers of the expansion of blockchain is the increasing demand for secure, tamper-proof, and transparent transactions. This has led to the development of various blockchain platforms, such as Ethereum, which helps in the development of decentralized applications or Apps for a variety of purposes from financial records to data storage. © 2024 IEEE.

关键词： Smart contract

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Regularized Hybrid Deep Learning for DDoS Attack Prediction in Software Defined internet of Things (SD-IoT) 3

Regularized Hybrid Deep Learning for DDoS Attack Prediction ...

引用

3rd international conference on Power, Control and computing Technologies, ICPC2T 2024

作者： Deepthy, J. Radhika, N. Denny, Alosh Department of Electronics & Communication Engineering Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham India Department of Computer Science and Engineering Amrita School of Computing Coimbatore Amrita Vishwa Vidyapeetham India School of Engineering Ernakulam Cochin University of Science and Technology Division of Computer Science and Engineering India

ISBN: (纸本)9798350349207

The availability of online resource is seriously threatened by the fatal DDoS (distributed Denial of Service) attacks, which can earnestly break up a targeted network or website by flooding it with traffic. DDoS attacks can use a variety of tactics and can be launched from different points around the world, making it difficult to predict when they will occur. In order to improve accuracy by minimizing overfitting of data in CNN, this work proposes an efficient method by combining CNN with Bi-LSTM for predicting DDoS attacks based on a modified loss function with regularization. We test our method on the CICDDOS2019 dataset of network traffic and demonstrate that it can accurately and successfully predict DDoS attacks with an accuracy of 99.8% and an F-score of 97.29%. © 2024 IEEE.

关键词： Denial-of-service attack

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Edge computing: Architecture, Implications and Future with Latest Trends 3

Edge Computing: Architecture, Implications and Future with L...

引用

3rd international conference on Pervasive computing and Social Networking, ICPCSN 2023

作者： Thakkar, Krish Patel, Akash Budhrani, Aishwariya Patel, Khushi Patel, Sachin Nayak, Amit Department of Information Technology Gujarat Changa388421 India Department of Computer Science & Engineering Gujarat Changa388421 India Department of Computer Engineering Gujarat Changa388421 India

ISBN: (纸本)9798350322842

As a result of the proliferation of internet-connected smart devices brought about by the explosive growth of the internet of Everything (IoE), lower bandwidth load, slower response, bad security, and poor privacy are just some of the issues that have arisen with data growth. Edge computing solutions have arisen as a response to the limitations of traditional cloud computing in meeting the data processing demands of modern societies. Edge computing, the new era of distributed computing, differs from cloud computing in that it places greater emphasis on being physically proximate to both the user and the data itself. The primary focus of this article is a critical examination of the associated literature and findings around edge computing. Edge computing is first briefly compared with cloud computing. Then, briefly discuss edge computing's architecture, followed by major challenges with edge computing and ending with latest trends with edge computing. © 2023 IEEE.

关键词： Computer architecture

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Malware Detection and Classification for internet of Things Using Self-Attention Based Long Short-Term Memory 3

Malware Detection and Classification for Internet of Things ...

引用

3rd IEEE international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Sudhakar, K. Husain, Saif O. Babu, D. Raja Kumar, M. Ashok Dineshkumar, R. Nitte Meenakshi Institute Of Technology Dept. Of Ai & Ds Bengaluru India College Of Technical Engineering The Islamic University Department Of Computers Techniques Engineering Najaf Iraq Sr University Department Of Electrical And Electronics Engineering Warangal India Skyline University Nigeria Department Of Computer Science Software Engineering And Cyber Security Kano State Nigeria Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Department Of Electronics And Communication Engineering Chennai India

ISBN: (纸本)9798350318609

The internet of Things (IoT) connects numerous intelligent devices providing security features that interact with default settings accessed through applications. Additionally, Deep Learning (DL)-based mechanisms was involved for malware detection to identify and mitigate attacks. The Adaptive Synthetic Sampling (ADASYN) technique addresses class imbalances, especially when splitter class instances are distributed data in complex patterns. The proposed Self-Attention based Long Short-Term Memory (LSTM) classification method facilitates the handling of long-range dependencies in transferred data sequences offering high flexibility and adaptability to varying input lengths. For feature selection Particle Swarm Optimization (PSO) is utilized iteratively optimizes a solution in a high-dimensional space although it may have a low convergence rate due to its iterative process. The obtained results demonstrate the proposed Self-Attention based LSTM model achieves better accuracy reaching 98.05% on the NSL-KDD dataset and 99.01 % on the UNSW-NB15 dataset. These results ensure accurate classification compared to other existing methods, such as Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). © 2024 IEEE.

关键词： internet of things

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Detection of False Information in Digital Media Using Blockchain technology 3

Detection of False Information in Digital Media Using Blockc...

引用

3rd Odisha international conference on Electrical Power Engineering, Communication and computing technology, ODICON 2024

作者： Kilaru, Aswini Prasad, L V Narasimha Ghantasala, G S Pradeep Ananthanagu, U. Kallam, Suresh Rajesh Sharma, R. Institute of Aeronautical Engineering Department of Cse Telangana Hyderabad India Alliance College of Engineering and Design Alliance University Department of Computer Science and Engineering Bengaluru India Center of Excellence in Immersive Technologies Alliance University Bengaluru India School of Computer Science and Engineering Jain Deemed to Be University Bengaluru India

ISBN: (纸本)9798350354379

The spreading of false information over the internet, highly impacts society and causes social and economic loss to the nation. One of the most important factors for the increase in the number of misleading information is that all the users of any particular digital platform usually do not verify the authenticity of the information. The principal impartial of this proposed work is to afford a solution to society to reduce the social and economic losses caused by spreading false information circulated digitally. Blockchain is a disseminated, decentralized network that conducts peer-to-peer transactions, meaning that it does not have a central entity to operate. Here we present a literature survey on various approaches towards this problem statement and investigate a Blockchain-based solution that focuses on all types of digital content by providing the end user to validate the information along with the evidence for data that was collected at each step. © 2024 IEEE.

关键词： distributed ledger

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Research on Employee Innovative Behavior Feedback System Based on Web-based ID3 Algorithm 3

Research on Employee Innovative Behavior Feedback System Bas...

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3rd international conference on Data Analytics, computing and Artificial Intelligence, ICDACAI 2024

作者： Luo, Hongchi School of Management Shanghai University Shanghai200444 China

ISBN: (纸本)9798331519032

In the internet era, the rapid development of technology has had a profound impact on the development of enterprises. With the rapid changes in the global economy, enterprises are faced with the serious challenges brought about by the uncertainty of market structure and demand. In this case, the innovative behaviour of employees has become a key factor to promote the development of enterprises, which is an important part of their innovative capacity. The study used the questionnaire star platform and offline distribution of questionnaires for enterprise employees with different gender, age, nature of the enterprise, job level and other attributes, and successfully distributed and returned 206 valid questionnaires, using SPSS 27, AMOS 25 and other analytical software to analyse the data for reliability analysis, validity analysis and correlation test, and using machine learning decision tree algorithm -ID3 algorithm to construct the decision tree model. This study can effectively help enterprises to recruit employees, through the comprehensive analysis of the attributes and innovative behaviour of employees, to achieve the accurate identification of employee potential, and then screen out high-quality talents with innovative ability for enterprises. © 2024 IEEE.

关键词： Adversarial machine learning

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Caching Techniques in Edge computing and Challenges 3

Caching Techniques in Edge Computing and Challenges

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3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Kumar, Sumit Dash, Yajnaseni Galgotias University Department of Computer Science & Engineering Uttar Pradesh India School of Computer Science Engineering and Technology Bennett University Uttar Pradesh India

ISBN: (纸本)9798350330724

Edge computing, a distributed computing concept, brings data processing and storage closer to endpoints or edge devices. Caching methods are crucial in edge computing environments for optimizing performance and minimizing latency and enable faster response times, efficient bandwidth utilization, and enhanced scalability. Edge computing uses caching techniques strategically based on user behaviour studies and access patterns to boost scalability and reduce network congestion. Caching techniques increase the efficacy and performance of edge computing. The parameters that influence efficacy include cache management strategies, network conditions, application features, and data access patterns. This paper presents a brief overview of the caching technologies utilized in edge computing and their challenges. © 2023 IEEE.

关键词： internet of things

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