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An Evaluation and Comparison for Phishing Attack Detection using Machine Learning Approaches 3

An Evaluation and Comparison for Phishing Attack Detection u...

引用

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

作者： Sharma, Ajeet Kumar Anushree Rakesh, Nitin Verma, Pawan Kumar Sharda University School of Engineering and Technology Dept. of Computer Science & Engineering Uttar Pradesh Greater Noida India GLA University Dept. of Computer Engineering & Applications Uttar Pradesh Mathura India Nagpur Campus Pune India

ISBN: (纸本)9798350309409

The persistent and evolving threat of phishing attacks demands effective and adaptive detection techniques. This research paper presents a comprehensive evaluation and comparison of various machine learning approaches to detect phishing attacks. We investigated five prominent algorithms: Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), Naive Bayes, and Extreme Gradient Boosting (XGBoost), to determine their efficacy in identifying phishing activities. Our methodology involved a systematic analysis using a large dataset of phishing and legitimate URLs, where each model was trained, tested, and validated to ensure robustness and reliability. The performance of each algorithm was assessed based on accuracy, precision, recall, and F1 score. Among the evaluated models, XGBoost demonstrated superior performance, achieving an exceptional accuracy of 99.75%. This result underscores the potential of XGBoost in phishing attack detection, offering a promising tool for cybersecurity applications. © 2024 IEEE.

关键词： Cybersecurity

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Advancements in Credit Scoring, Profit Scoring, and Portfolio Optimization for P2P Lending 3

Advancements in Credit Scoring, Profit Scoring, and Portfoli...

引用

3rd international conference on Communication, control, and Intelligent Systems, CCIS 2024

作者： Nayaka, Premkumar Hegde, Anusha Bhowmik, Biswajit National Institute of Technology Karnataka Ishwarchandra Vidyasagar Ait Lab Brics Laboratory Department of Computer Science and Engineering Surathkal India National Institute of Technology Karnataka Brics Laboratory Department of Computer Science and Engineering Surathkal India

ISBN: (纸本)9798331528201

The Peer-to-peer (P2P) lending platform allows borrowers to connect directly with lenders outside traditional banking systems. Therefore, for the sustainability of these platforms, they must accurately assess the credit risk and profitability of the loans. Various credit scoring techniques, including Logistic Regression, neural networks, and ensemble methods, can be used to estimate the likelihood of borrower default. It is imperative to analyze the profit the lenders generated and enhance the credit scoring so that the investors face minimum loss. Once the profit analysis is done, then it is crucial to advise the investors about the portfolio of loans. This paper presents recent credit scoring, profit scoring, and portfolio optimization trends for P2P lending. We highlight the significant issues in incorporating machine learning models into credit scoring systems. The analysis emphasizes the need for a data-driven approach to perfecting lending practices, thus benefiting both borrowers and investors in the rapidly changing P2P landscape. © 2024 IEEE.

关键词： Decentralized finance

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Development of a Real Time vision-Based Hand Gesture Recognition System for Human-computer Interaction 3

Development of a Real Time Vision-Based Hand Gesture Recogni...

引用

3rd IEEE Applied Signal Processing conference, ASPCON 2023

作者： Das, Arijit Maitra, Kaulik Roy, Shayan Ganguly, Biswarup Sengupta, Meghna Biswas, Shreya Meghnad Saha Institute of Technology Electrical Engineering Department Kolkata India National Institute of Technology Silchar Electrical Engineering Department Assam India National Institute of Technology Rourkela Clavictor Academy Private Limited Odisha India

ISBN: (纸本)9798350325881

Speech impairment, a debility that affects an individual's capacity to communicate via talking and hearing. Therefore, sign language is essential for facilitating communication with individuals who are deaf and mute. American Sign Language (ASL) is widespread in the application of sign language worldwide, with regional variations. Our proposed system is a vision-based hand gesture recognition software, where the camera and the software will observe the set of sign language or gestures and will convert it into normal text. So, with the help of this software, we can easily communicate with a mute person. In the proposed system we used ASL as the language dataset and YOLO-v5 as the main algorithm model. We also included a 'BOT' control with our gesture recognition system of hand for a better understanding of the power of the model and different application abilities of hand gesture recognition. Service bots have one-on-one conversations with users and discover "natural"and intuitive interfaces. The main highlighting point is we can use a custom dataset as per our flexibility, for example, we can move the bot forward by giving a sign like '1' instead of sign language like 'A' or 'B'. We captured nearly 700 pictures of sign language with different backgrounds and trained it where we got an overall 93% accuracy in the experiment. © 2023 IEEE.

关键词： Human computer interaction

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Stroktor-A System to Predict Ischemic Brain Stroke using Learning Techniques 3

Stroktor-A System to Predict Ischemic Brain Stroke using Lea...

引用

3rd IEEE international conference on Intelligent Technologies, CONIT 2023

作者： Karnavat, Rachna A. Patole, Eshwari B. Parkhi, Apurva S. Muluk, Manasi A. More, Surabhi J. Pune Institute of Computer Technology Information Technology Department Maharashtra Pune India

ISBN: (纸本)9798350338607

According to WHO, over 15 million people suffer from a stroke which causes 5 million deaths and approximately 30% of survivors are facing serious disability. CDC (Centers for Disease control and Prevention) has identified stroke as the fifth-leading cause of death globally. More than 70% of strokes are first events, hence making primary stroke prevention is particularly an important aspect. With the availability of a system to detect the brain stroke with the early symptoms occurring in patients would lead to early diagnosis and prevent severe consequences. This research work is dedicated to build a system that would detect brain stroke with premature symptoms and generate accurate results using neural networks and computer vision. Considering the severity of stroke, it is necessary to immediately consult medical practitioners to prevent the consequences which is a tough task. This state of art focuses on obtaining stroke possibility based on change in facial features as prominent symptoms and providing immediate precautionary measures. Along with this, providing an interactive platform for users to connect with available doctors using video calling for immediate consultation. © 2023 IEEE.

关键词： Diagnosis

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Face Mask Recognition Based on YOLOv3-tiny 3

Face Mask Recognition Based on YOLOv3-tiny

引用

3rd international conference on Electronic Communication and Artificial Intelligence, IWECAI 2022

作者： Dai, Wei Wang, Jing Ren, Tao Zhu, ZiXuan School of Economics Wuhan University of Technology Hubei Wuhan China

ISBN: (纸本)9781665479974

The use of computer vision to realize non-contact face mask wearing testing and identify the standardization of wearing can improve the efficiency of mask wearing inspection, which is of great significance to reduce the spread of COVID-19. Based on the YOLO v3 framework in deep learning, this project conducts an in-depth study on the accuracy and efficiency of face mask detection, introduces its structure and principle, and explores and experiments its application based on TensorFlow. The evaluation and identification rate of the experiment was 78∗, which verified the feasibility and practicability of the method. © 2022 IEEE.

关键词： Object detection

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Based-on computer vision Applications for Bus Stop Passenger Detection System 3

Based-on Computer Vision Applications for Bus Stop Passenger...

引用

3rd IEEE international conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2023

作者： Chang, Yu-Cheng Tsai, Hua-Wen Huang, Chao-Yi Wu, Zong-Rong Department of Computer Information and Network Engineer Lunghwa University of Science and Technology Taiwan Department of Bachelor's Program in Intelligent Robot National Yunlin University of Science and Technology Taiwan

ISBN: (纸本)9798350333862

Passenger transport is one of the most common ways of commuting in Taiwan. It plays an important role in the transportation system due to its large number of stations, dense frequency, and cheap transportation. Due to the unfriendly transportation environment and a large number of passengers, a blind spot of passenger transportation exists, which leads to traffic accidents at the station. We research to make the Bus Stop Passenger Detection System. Taking the object detection of Wheelchairs into consideration, it is more convenient to assist the disabled to find the passenger transportation system, which makes Taiwan's transportation system more convenient. © 2023 IEEE.

关键词： Object detection

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MVPD: A Multimodal Video Physiology Database for rPPG 3

MVPD: A Multimodal Video Physiology Database for rPPG

引用

3rd IEEE international conference on Software Engineering and Artificial Intelligence, SEAI 2023

作者： Peng, Jiahe Su, Weihua Tian, Zandong Zang, Dongyuan Li, Xiaoyu Song, Zijing Hebei University of Technology School of Artificial Intelligence Tianjin China Hebei University of Technology School of Mechanical Engineering Tianjin China

ISBN: (纸本)9798350337952

During the era of rapid development in the field of computer vision, camera sensors have been applied to a variety of scenarios, able to capture states and movement changes of objects, and even observe nuances in the real world that are invisible to human eyes. Remote photoplethysmography (rPPG) is a camera-based non-contact sensor method for monitoring physiological signs. In recent years, there are few datasets for rPPG and most of them are only for a few physiological parameters, such as photoplethysmography (PPG), heart rate (HR) and peripheral oxygen saturation (SpO2). For studying more vital signs and learnable parameters, we propose the Multimodal Video Physiology Database (MVPD) containing videos and physiological information from 13 volunteers. We use cameras to collect videos of face, palm, wrist and fingertip, and physiological sign parameters such as electrocardiogram (ECG), respiratory rate (RR), skin temperature (ST), PPG, pulse rate (PR), blood pressure (BP), and SpO2. This database is mainly used for studying rPPG. © 2023 IEEE.

关键词： computer vision

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A DEFORMABLE 3D ZEBRAFISH MODEL FOR BRIGHT-FIELD MICROSCOPY IMAGE SIMULATION 18

A DEFORMABLE 3D ZEBRAFISH MODEL FOR BRIGHT-FIELD MICROSCOPY ...

引用

18th international conference on Interfaces and Human computer Interaction 2024, IHCI 2024, the 17th international conference on Game and Entertainment Technologies 2024, GET 2024 and the 18th international conference on computer Graphics, Visualization, computer vision and Image Processing 2024, CGVCVIP 2024, Part of the 18th Multi conference on computer Science and Information Systems 2024, MCCSIS 2024

作者： Jámbor, Richárd Tanács, Attila Dept. of Image Processing and Computer Graphics Institute of Informatics University of Szeged Árpád tér 2. SzegedH-6720 Hungary

ISBN: (纸本)9789898704580

Due to their rapid reproduction, development, and similar genetic structure to humans, zebrafish are popular animals in various biological research. Their small size and body transparency make them convenient to examine under a bright-field light microscope. However, these provide 2-dimensional projected images, which makes 3D measurements difficult. Usual approaches try to reconstruct 3D structures from series of projected images, that is not always an option. In our paper we propose an approach to model the images acquisition process including the 3D parametric deformable model of the zebrafish and the light conditions in the microscopy environment. Our goal is to simulate images that look similar to the real ones using only a few parameters. © 2024 Interfaces and Human computer Interaction. All Rights Reserved.

关键词： Invertebrates

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Policy Iteration Based Microgrid Frequency control 3

Policy Iteration Based Microgrid Frequency Control

引用

3rd international conference on Power Systems and Electrical Technology, PSET 2024

作者： Kim, Byungchul Abed, Eyad H. University of Maryland Department of Electrical and Computer Engineering College ParkMD United States

ISBN: (纸本)9798350353204

Microgrid inverter control shall be more efficient if the systems are controlled without system parameters owing to influenced by disturbances from other systems. We concentrate on solving optimal nonlinear input affine system via reinforcement learning. We express input-to-state stability (ISS) and fixed admissibility (FA) of the input affine system with the policies created by integral policy iteration (IPI). However, previously mentioned approaches need the system parameters to control the systems. Due to these constraints, on account of three online explorized IPI and integral Q-learning A, B are suggested, all of them create the same convergent succession within the vital excitation status on the exploration. All the suggested approaches are fully or partially model free and can concurrently explore the state-space in a stable way during the online learning sequences. Finally, we simulate the proposed approaches within microgrid inverter fault ride through on transient stability to verify performance. © 2024 IEEE.

关键词： Microgrids

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Deep Learning Driven X-ray Classification for Pneumonia Detection Using CNN 3

Deep Learning Driven X-ray Classification for Pneumonia Dete...

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3rd international conference on Communication, control, and Intelligent Systems, CCIS 2024

作者： Saxena, Sarvagya Khandelwal, Siddhartha Chaudhary, Sneha Gupta, Priyanka Gla University Computer Science Engineering Vrindavan India Gla University Computer Science Engineering Mathura India Gla University Computer Engineering & Application Mathura India

ISBN: (纸本)9798331528201

Major deaths (55% or 1.5 million) of LRI (Lower Respiratory Infections) are caused due to Pneumococcal pneumonia. LRI is the 5th highest cause of demise as mentioned by the Global Burden of Disease Study 2015. Health organization suffers from a lack of Physicians. A Physician handles so many cases which leads to misdiagnoses. To resolve all these issues we came up with an easy-to-handle, and implemented in health organizations, the CNN model. The main aim of this model is to help the healthcare professionals by providing them with a tool which will help them detect Pneumococcal pneumonia. With the help of this tool, the work strain of a doctor can be reduced. This model is developed without any pre-trained model and for better accuracy, an immense dataset is used. All the X-ray images were pre processed before being introduced to the neural network. Different layers have been used to make the model more precise and make it adaptable for X-ray images under different conditions. The aim is to combine deep learning concepts with healthcare to make a positive and meaningful impact in the healthcare industry. © 2024 IEEE.

关键词： CNN Models Deep Learning Healthcare Pneumococcal pneumonia X-Ray

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