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A Robust Security Detection Strategy for Next Generation IoT Networks

computers, Materials & Continua 2025年第1期82卷 443-466页

作者： Hafida Assmi Azidine Guezzaz Said Benkirane Mourade Azrour Said Jabbour Nisreen Innab Abdulatif Alabdulatif Technology Higher School Essaouira Cadi Ayyad UniversityEssaouira44000Morocco IMIA Laboratory MSIA TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknesErrachidia50050Morocco CRIL-CNRS Artois UniversityLens62300France Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityDiriyahRiyadh13713Saudi Arabia Department of Computer Science College of ComputerQassim UniversityBuraydah52571Saudi Arabia

Internet of Things(IoT)refers to the infrastructures that connect smart devices to the Internet,operating *** connectivitymakes it possible to harvest vast quantities of data,creating new opportunities for the emergence of unprecedented *** ensure IoT securit,various approaches have been implemented,such as authentication,encoding,as well as devices to guarantee data integrity and *** these approaches,Intrusion Detection Systems(IDS)is an actual security solution,whose performance can be enhanced by integrating various algorithms,including Machine Learning(ML)and Deep Learning(DL),enabling proactive and accurate detection of *** study proposes to optimize the performance of network IDS using an ensemble learning method based on a voting classification *** combining the strengths of three powerful algorithms,Random Forest(RF),K-Nearest Neighbors(KNN),and Support Vector Machine(SVM)to detect both normal behavior and different categories of *** analysis focuses primarily on the NSL-KDD dataset,while also integrating the recent Edge-IIoT dataset,tailored to industrial IoT *** results show significant enhancements on the Edge-IIoT and NSL-KDD datasets,reaching accuracy levels between 72%to 99%,with precision between 87%and 99%,while recall values and F1-scores are also between 72%and 99%,for both normal and attack *** the promising results of this study,it suffers from certain limitations,notably the use of specific datasets and the lack of evaluations in a variety of *** work could include applying this model to various datasets and evaluating more advanced ensemble strategies,with the aim of further enhancing the effectiveness of IDS.

关键词： IoT security intrusion detection RF KNN SVM EL NSL-KDD Edge-IIoT

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Web-plugin to Detect Clickbait in News Articles using RNN and LSTM 5

Web-plugin to Detect Clickbait in News Articles using RNN an...

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5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Krishneth, A. Dharaneesh, J.D. Jisnu, S. Sivaganesan, D. Psg Institute of Technology and Applied Research Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350321425

'Clickbaits' are either false or misleading headlines that aim to attract users' attention and entice them to click on a link or a news article that isn't really interesting as the title makes it up to be. A clickbait title can degrade the user experience and spread disinformation or misinformation on the Internet. In this study, a novel approach for Clickbait detection in news articles using machine learning technique of Recurrent Neural Network and Long-Short Term Memory is proposed. The clickbait detection process takes place in two distinct steps, first to identify the headlines in a website using a web plug-in, these headlines are then fed into a machine learning model which can predict if the headline is a clickbait or not. This a binary classification problem where the model is trying to predict which of the two categories the input belongs to. The algorithm is put into action using a web plugin which is triggered when popular news websites are visited and fetch the headlines using DOM method, the headlines are then sent to the server for prediction upon which the headlines get marked either red or green which indicates the headlines to be either clickbait or not respectively which, this makes the user aware if a headlineis clickbait or not with just a glance. The result obtained by the above method is an improvement over the existing methods and the user interface provided by the web plugin removes any manual labor from the user side and offers an engaging yetsimplistic user experience. © 2023 IEEE.

关键词： Long short-term memory

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A review of research on super-resolution image reconstruction based on deep learning 8

A review of research on super-resolution image reconstructio...

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8th International Conference on Intelligent Informatics and Biomedical sciences, ICIIBMS 2023

作者： Yu, Wanjun Liang, Xiayan Shanghai University of Applied Technology School of Computer Science and Information Engineering Shanghai China

ISBN: (纸本)9798350369564

Currently, Super-resolution image reconstruction (SRIR or SR) is a research hotspot in the field of computer vision and image processing. With the development of deep learning, The technology of super-resolution image reconstruction based on deep learning has achieved some research results. In this paper, the concept of super resolution image reconstruction and typical deep network models of super resolution image reconstruction are described first, and then the advantages and disadvantages of different models are compared and analyzed. On this basis, the future of super-resolution image reconstruction methods based on deep learning is forecasted. © 2023 IEEE.

关键词： Generative adversarial networks

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Simulating Home Appliance Behavior and Operational Condition-Action Rules for Autonomous Intelligence 3

Simulating Home Appliance Behavior and Operational Condition...

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3rd International Conference on Intelligent Computing and Next Generation Networks, ICNGN 2024

作者： Ehimwenma, Kennedy Efosa Ji, Haowen Jinle, Lin Sharji, Safiya Al Cheraghy, Maryam Bowen, Yu Dept of Computer Science College of Science Mathematics & Technology Wenzhou Kean University Wenzhou China Information Technology Dept University of Technology & Applied Sciences Muscat Oman

ISBN: (纸本)9798331529222

The future of home appliances in the IoT (Internet of Things) lies in self-awareness, independent condition-action rule implementation, and device autonomy. In the concept of autonomy, agent-based IoT appliances can SLEEP and WAKE-UP independently as when necessary, perceive and compute data;and engage in communication or negotiation with other agent-based devices. In the paradigm of OOP, this paper describes various home appliances' autonomous artificial intelligent (AAI) behavior. While self-awareness borders on the appliance knowing its current status and location, self-control relates to the appliance's ability to control its outgoing and incoming data and take the appropriate action based on some given environment data conditional rules. Thus, this paper presents some IoT home appliances' operational condition-action behavior (CAB). Firstly, by simulation, then followed by the actual transformation of the CAB rules into modular programs in object-oriented paradigm for sensor and appliance agents. The WindSpeedSensor, TempSensor, and HumiditySensor utilize the given environment data input to communicate with their respective WindowAppliance and CoffeeMachineAppliance agent, as demonstrated in this paper. In turn, the appliance agents take the decision reached by their sensors to perform some autonomous action. This model depicts independent AAI behavior of home appliances for the benefit of home owners. ©2024 IEEE.

关键词： Domestic appliances

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Home Automation with Webserver Deployment with Raspberry Pi Pico 2

Home Automation with Webserver Deployment with Raspberry Pi ...

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2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Shabariram, C.P. Venkateshwaran, M. Abinesh, R. Manoranjith, R. Department of Computer Science and Engineering PSG Institute of Technology and Applied Research Coimbatore India

ISBN: (纸本)9798350340235

Home Automation system with web server deployment is developed using Raspberry Pi Pico and micropython, which turns ON the lights based on the count of persons inside that particular room. The system uses Infrared Red (IR) sensor, which detects the heat radiation in the environment. This heat radiation is not constant as it changes due to the movement of people in the sensing environment. This change is used as a measure to detect the changes in the environment which allows us to perform a particular action for the event. The data is sent to node which sends the data to the webserver running in the Raspberry pi pico. Based on the result, the light is turned ON or OFF. © 2023 IEEE.

关键词： Home Automation Infrared sensor Micropython Raspberry Pi Pico Webserver

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Toddler Activity Analysis Using Machine Learning

Toddler Activity Analysis Using Machine Learning

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2023 International Conference on Intelligent Systems for Communication, IoT and Security, ICISCoIS 2023

作者： Kala, I. Bhuvaneswari, P. Dharun, R. Dharshini, S. PSG Institute of Technology and Applied Research Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350335835

Toddler activity recognition aims in finding out the activities of toddler and also toddlers based on the video captured by camera. The purpose of activity recognition is to monitor a new employee of the company (maybe a software or even a restaurant) whether employees are working properly or do we need to give more training. This system can also be used by the parents to monitor the activity of the kids who are alone at home. This system can also be implemented in hospitals to monitor the patients and to check their improvement. Toddler activity recognition system is developed using CNN and LSTM. To predict the activity the path of the video file is given as input. The predicted result by the model is checked for accuracy. To make the result available for the end user (who needs to monitor the activity) and can access the result through two ways. In the First method user can directly view on the system where the model is predicting the result. In the second method user is out of station, so the predicted result will be updated on the cloud on fixed time intervals and user can view the result from the working place itself. © 2023 IEEE.

关键词： Personnel training

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Detection of Mango Leaves Disease using CSUBW based Residual Attention with EfficientNet 2

Detection of Mango Leaves Disease using CSUBW based Residual...

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2nd International Conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Kumar V, Sunil Jyothi, A.P. Nagamani, H.S. Sumanth, S. Nitte Meenakshi Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India Ramaiah University of Applied Sciences Faculty of Engineering and Technology Department of Cse Bengaluru India Department of Computer Science Bengaluru India Department of Computer Science and Computer Applications Kolar India

ISBN: (纸本)9798350382952

Mangoes are one of the most popular fruits worldwide due to their taste and nutrition. Plant diseases may reduce plant quantity and quality. Disease management to improve crop quality and productivity requires early plant illness detection. Automation of plant disease detection reduces large farm surveillance. Since plants feed us, leaf problems must be diagnosed quickly and accurately. Our advanced learning method automatically detects leaf disease in several mango plant varieties. This study creates the RAM-EfficientNet, a novel illness classification network. The RAM block in EfficientNet extracts additional features and handles slight leaf lesion changes. Transfer learning was used to train EfficientNet on ImageNet to overcome the mango leaf disease sample size issue. The Cat Swarm Updated Black Widow Model (CSUBW), a hybrid optimization model, changes RAM-EfficientNet's weights to improve classification accuracy. Black Widow Optimization Algorithm (BWO) and Cat Swarm Optimization Algorithm (CSO) are combined to create the hybrid optimization model. The model's performance is then assessed to confirm its efficacy. © 2024 IEEE.

关键词： Fruits

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DeltaBin: An Efficient Binary Data Format for Low Power IoT Devices

DeltaBin: An Efficient Binary Data Format for Low Power IoT ...

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2023 IEEE International Conference on computer, Information, and Telecommunication Systems, CITS 2023

作者： Maleki, Neda Musaddiq, Arslan Mozart, David Olsson, Tobias Omareen, Mustafa Ahlgren, Fredrik Linnaeus University Applied IoT Lab Department of Computer Science and Media Technology Sweden

ISBN: (纸本)9798350336092

The Internet of Things (IoT) notion is quickly influencing t he architectures of data-driven systems d ue to the ever-increasing rapid technological progress in all sectors. The IoT involves the collection and exchange of data from a large number of interconnected devices or sensors. The collected data is structured and transmitted in a variety of different data formats such as JSON, CBOR, BSON, or simply a binary format. The data format used by an IoT device can have a significant i mpact on t he efficiency of its data transmission. In general, using a more compact and efficient data format can help to reduce t he amount of data that needs to be transmitted, which can improve the overall speed and performance of the device. For example, using a binary data format rather than a text-based format can often result in smaller data sizes and faster transmission times. Similarly, using a binary format in a more compressed form can further help to reduce the size of the data being transmitted, which can further improve the efficiency of the transmission. In this paper, we propose Delta Binary (i.e., DeltaBin) to reduce the binary data format by transmitting only changed data. We assess DeltaBin using a real IoT deployment scenario. © 2023 IEEE.

关键词： Internet of things

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Fake Product Identification using Blockchain 14

Fake Product Identification using Blockchain

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Hemkiran, S. Prakash Ramanathan, R.M. War, Mohammad Mudasir Aadhithiyan, K.S. Psg Institute of Technology and Applied Research Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350335095

Manufacture and sale of counterfeit goods has been plaguing several business sectors for many years. The production of counterfeit goods are increasing, this has an impact on the sales and earnings of the businesses. By stifling revenues, economic growth, and consumer health, it has an impact on governments, global trade, businesses, and consumers. The current technology used for combating counterfeit goods rely on a centralised authority. Issues with this design include single point processing, failure, and storage. Blockchain technology has can be used as an alternative to address all these issues for these *** code can be used along with a blockchain hash code to uniquely identify every single product that ever enters the supply chain, hence no fake product can flood the supply chain. Ethereum blockchain is utilized and smart contracts are deployed to store the data about each and every product. Each products whole history can be tracked by using its QR code. © 2023 IEEE.

关键词： Smart contract

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Online Legal Literacy Platform 1

Online Legal Literacy Platform

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1st International Conference on Intelligent Technologies for Sustainable Electric and Communications Systems, iTech SECOM 2023

作者： Kala, I. Hariharan, K. Kavisri, S. Kaviyarasu, D. Psg Institute of Technology and Applied Research Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350371185

The Motor Vehicle Act is a complex legal framework that regulates various aspects of motor vehicle usage in India. However, many individuals lack knowledge and understanding of the Act, which can lead to unsafe driving practices, non-compliance with regulations, and legal violations. Furthermore, the Act is subject to frequent amendments, making it challenging for individuals to stay up to date on the latest regulations. To address these issues, this project proposes an Online Legal Information Platform for the Motor Vehicle Act. The platform utilizes advanced technologies such as BERT fine-tuning and natural language processing techniques to match user input scenarios with relevant sections of the Act. Users can input their scenarios and the platform suggests the ideal law that can be utilized in the given situation. The system displays matching laws with their title and description and generates a summary for the selected law to facilitate easy comprehension. Additionally, voice-to-text feature is incorporated in order to assist people with visual impairments. The platform aims to bridge the gap between legal language and everyday usage, promoting better compliance with road safety laws. The system will be user-friendly and accessible to individuals with limited legal knowledge, making it easier for them to navigate the legal system. Future work includes expanding the platform to include other regional languages as well to increase its availability to people all around the nation. © 2023 IEEE.

关键词： User interfaces

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