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8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Patil, Chaitra Nagaraja, G.S. Rv College of Engineering Dept of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331505462

The project labelled 'DOH Integrator tool' aims to improve internet privacy and security by implementing the DNS over HTTPS (DoH) protocol. Traditional DNS queries are sent in cleartext, which makes them subject to eavesdropping and manipulation. This project tries to address these vulnerabilities by encapsulating DNS traffic within HTTPS, encrypting the requests and responses sent between client devices and DNS servers. The study discusses high-level design issues like user interface features, error management, and system architecture. It describes the implementation process, highlighting the programming languages and tools utilized, including JavaScript, HTML, CSS, and Bootstrap. The project also includes testing procedures to ensure that the application is reliable. © 2024 IEEE.

关键词： HTTP

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Intelligent System for Detection of Intrusion in Imbalanced Network Traffic 14

Intelligent System for Detection of Intrusion in Imbalanced ...

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14th International Conference on Cloud Computing, Data science and engineering, Confluence 2024

作者： Bagla, Piyush Mishra, Amit Kumar Pandey, Neeraj Kumar Sharma, Ravi Dumka, Ankur National Institute of Technology Department of Computer Science & Engineering Jalandhar India Graphic Era Hill University Dept. of Computer Science & Engineering Dehradun India Department of Computer Science & Engineering Dehradun India Women Institute of Technology Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350344837

Malicious cyberattacks can frequently hide among enormous amounts of regular data in networks with uneven traffic patterns. The identification of imbalance network traffic is difficult to find and making a challenge in terms of Signature building. Despite years of improvement, IDSs still struggle to increase detection accuracy. There are distinct machine learning or deep learning algorithms provides the better results and accuracy for imbalance network traffic. In this study, intrusion detection in unbalanced network traffic is accomplished using both machine learning and deep learning. This process a DSSTE algorithm to avoid imbalance problems. Initially the training set is pre-processed to modify imbalanced data and features are extracted. The proposed model is evaluated with trained data using multiple classification algorithms. © 2024 IEEE.

关键词： Intrusion detection

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Care Compass: Monitoring made easy, Care made effective 3

Care Compass: Monitoring made easy, Care made effective

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3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Manhas, Prabal Chandra, Joydeep Kaur, Ramanjot Sahay, Rashi Chandigarh University Punjab India Chandigarh University Dept.of Computer Science and Engineering Punjab Mohali India Manav Rachna International Institute of Research and Studies Faridabad India

ISBN: (纸本)9798331515911

Traditional healthcare focused on hospitals and clinics proved out to be inadequate, especially during the COVID-19 pandemic and various emergency crisis, Care Compass, is an innovative and affordable smart wearable device aimed at addressing critical health challenges faced by today's youth. The 21st century witnessed a large-scale transformation with the integration of Internet of Things and smart devices ranging from healthcare to manufacturing sector. The device integrates smart IoT devices and other technologies such as cloud computing platforms, health management mobile application with machine learning algorithms, offering real-time personalized health recommendations and continuous monitoring of vital health parameters. Emphasis is placed on accessibility and affordability, making Care Compass a viable solution for a broader demographic. The integration of Care Compass with clinical workflows is facilitated through collaboration with healthcare providers, enhancing the utility and effectiveness of the device in real-world applications. The results from initial testing demonstrate the potential of Care Compass to significantly improve health outcomes and quality of life for young individuals. © 2025 IEEE.

关键词： Electronic health record

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Comparative Analysis of Deep Learning Algorithms for Handwritten Digit Recognition 3

Comparative Analysis of Deep Learning Algorithms for Handwri...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Savaram, Padmaja Bandu, Sasidhar Lakshitha, B. Prince Sattam bin Abdulaziz University Dept.of Computer Science Al-Kharj Saudi Arabia Prince Sattam bin Abdulaziz University Dept. of English Al-Kharj Saudi Arabia Vnrvjiet Jntu Dept. of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798331518592

Handwritten digit recognition presents a considerable challenge in pattern recognition due to the inherent variability in digit size, stroke width, orientation, and margin alignment. The difficulty is further exacerbated when different individuals write the same digit with varied stylistic nuances. Discriminating between visually similar digits, such as 1 and 7, 5 and 6, 3 and 8, 2 and 5, and 2 and 7, adds an additional layer of complexity. The offline handwritten digit recognition approach discussed in this paper leverages a range of machine learning methodologies. The objective is to establish robust and accurate digit recognition techniques, utilizing several algorithms including Artificial Neural Networks, Convolutional Neural Networks, K-Nearest Neighbors, and Recurrent Neural Networks. These algorithms are evaluated using the Modified National Institute of Standards and Technology (MNIST) dataset and the US Postal Service (USPS) dataset to identify the most effective model. The selection of the optimal machine learning approach is determined by factors such as dataset size, data complexity, and required accuracy. The Convolutional Neural Networks model demonstrated superior performance, achieving an accuracy of 98.58% with 10,000 MNIST images and 94.7% accuracy with 2007 USPS images when compared with other models. © 2024 IEEE.

关键词： Contrastive Learning

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Spider monkey ınspired optimization algorithm based clustering for face recognition

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International Journal of Information Technology (Singapore) 2024年 1-13页

作者： Gopal, Veni devi Devi, G. Shree Geetha, Angelina Department of Computer Science and Engineering B S Abdur Rahman Institute of Science & amp Technology Chennai India Department of Computer Science and Engineering Hindustan Institute of Science and Technology Chennai India Dept of Computer Applications BSA Crescent Institute of Science and Technology Chennai India

Face recognition is a fast-growing technology that is widely used in forensics such as criminal identification, secure access, and prison *** contrasts from other classification issues in that there are normally a more number of classes in face recognition. Thus, the validation accuracy of the conventional subsystem face recognition is unsuitable. In order to overcome the problems that are likely to be encountered, the proposed method utilizes the Spider Monkey inspired Optimization (SMO) algorithm for face clustering and recognition. At first feature reduction is done by Advance Principal Component Analysis (APCA) which is a hybridization of PCA and linear discriminant analysis (LDA). After reducing the features, the selected features are grouped and faces are recognized by means of SMO algorithm. From the food search behavior of spider monkeys, SMO algorithm is developed. The performance of the proposed method is evaluated by means of sensitivity, specificity, and accuracy. Here the proposed method accomplishes 98.66% accuracy. Using the MATLAB platform, the recommended technique is implemented. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Accuracy Linear discriminant analysis Principal component analysis Sensitivity Specificity Spider monkey optimization

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An Effective Method to Detect DHCP Starvation Attack using Port Scanning

An Effective Method to Detect DHCP Starvation Attack using P...

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2023 International Conference on Next-Generation Computing, IoT and Machine Learning, NCIM 2023

作者： Jony, Asaduzzaman Miah, Abu Saleh Musa Islam, Muhammad Nazrul Dept. of Computer Science and Engineering Dhaka Bangladesh The University of Aizu Dept. of Computer Science and Engineering Aizuwakamatsu Japan Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350316001

Nowadays, the DHCP starvation attack is a crucial attack that denied the services for the legitimate network user where the attacker mainly occupies all the IP addresses in the DHCP server pool. Most of the existing studies proposed ICMP (Internet Control Message Protocol) and the ARP (Address Resolution Protocol) based techniques to detect the DHCP starvation attack. However, the ICMP-based detection is ineffective if the client has an active host-based firewall that blocks the ICMP ECHO REQUEST, while the ARP-based detection does not work for DHCP networks separated by a DHCP relay agent and works only within the same or local network. Therefore, the objective of this research is to propose an effective technique to detect DHCP starvation attack detection through port scanning to address the limitations of ICMP and ARP-based detection methods. To attain this objective, this study first highlights the limitations of existing detection methods demonstrating insightful facts. Secondly, the study proposed a port scan-based DHCP starvation attack detection method for local and remote (relay) DHCP networks. Finally, the effectiveness and validation of the proposed techniques were demonstrated using the Multivendor Network Emulation Software (EVE-NG). The study showed that the proposed port scanning-based technique could accurately detect the DHCP starvation attack while overcoming the limitations of the ICMP and ARP techniques. © 2023 IEEE.

关键词： Network security

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Classification and Prediction of Alzheimer's Disease using Deep Learning 7

Classification and Prediction of Alzheimer's Disease using D...

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7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Brindha, D. Ebenezer, V. Selvaraj, E. Jackson Bevin Geoff, D.M. Dileep, B. Bethina Nambi, M. Thirumalai Dept. of Computer Science and Engineering Coimbatore India Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350397253

This study has proposed a novel technique for performing object detection and image classification with a Convolutional Neural Network (CNN) architecture. Nevertheless, employing a 2D CNN architecture to identify a lot of patients as AD or MCI based on 3D MR Images becomes challenging when dealing with hundreds of MRI images that are highly similar in nature. It provides a solution to this problem that streamlines the concept of classification of patients based on 3D MRI by exploiting 2D data produced by the CNN structure. In this method, 2D characteristics from MRI are extracted and then converted by using an appropriate Machine Learning (ML) algorithm for categorization. © 2023 IEEE.

关键词： Magnetic resonance imaging

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Chatbot Based on Emotions Using Deep Learning 1

Chatbot Based on Emotions Using Deep Learning

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1st International Conference on Optimization Techniques for Learning, ICOTL 2023

作者： Nirupa, V. Renuka, G.B. Naga Lakshmi, B. Sumanth Kumar, C.P. Rudra Sekhar Reddy, A. Paramesh, J. Dept. of Computer Science & Engineering Madanapalle India Dept. of Computer Science & Engineering Anantapur India

ISBN: (纸本)9798350328042

Human emotions are unpredictable as they change very frequently. Human emotions areinvoluntary mental states of feelings and are accompanied by physiological changes. Emotions which can be detected through the facial expressions play a major role and are very much important for non-verbal communication as they reflect on their faces. In the process of developing computer modeling of human's emotions, a lot researches have been made. Therefore, a chatbot detecting the emotions can be a better approach for detecting emotions. In this study, it demonstrate that Convolutional Neural Networks (CNNs) offer a superior method for detecting human emotions and develop a deep learning model that can accurately classify the facial expressions. The FER 2013 dataset was used in this study's training. The evaluation of the suggested approach produces pretty accurate findings, which could inspire academics to develop a Chabot model based on emotions in the future. © 2023 IEEE.

关键词： Convolutional neural networks

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Detection of Lung Inflammation using Chest X-ray with Deep Learning Algorithm 7

Detection of Lung Inflammation using Chest X-ray with Deep L...

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7th International Conference on Communication and Electronics Systems, ICCES 2022

作者： Singh, K. Purushotham Kumar, B. Niranjan Anil, A. Rajendran, Selvi Dept.of Computer Science and Engineering Chennai India Hindustan Institute of Technology and Science India

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

Lung Inflammation causes the passing of around 700,000 youngsters consistently and influences 7% of the worldwide populace. Chest X-ray images are principally utilized for the analysis of this infection. Notwithstanding, in any event, for a prepared radiologist, it is a moving errand to look at chest X-ray. There is a need to further develop the determination precision. In this work, an effective model is developed for the recognition of pneumonia from the computerized chest X-ray pictures is proposed. Several methods are utilized to expand the preparation of dataset in a decent manner. Consequently, it is more advantageous to fabricate a computerized indicator to anticipate the pneumonia utilizing the large information profound learning strategies. Among the wide range of various procedures, Convolutional Neural Networks stand tall and high in this forecast alongside different classifiers. Convolutional brain network comprising of convolution and pooling layers and completely associated Softmax layers toward the finish to give the last forecast. © 2022 IEEE.

关键词： Forecasting

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Cybersecurity: Threats, Requirements, Deployments, Techniques, System Architecture, and Future Research

Cybersecurity: Threats, Requirements, Deployments, Technique...

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2024 International Conference on Smart Devices, ICSD 2024

作者： Yadav, Ajay Karnatak, Vijay Mishra, Amit Kumar Verma, Shalini Aswal, Pallaw Singh Tripathi, Neha University Institute of Computing Chandigarh University Punjab Mohali India THDC Institute of Hydropower Engineering and Technology Dept. of Computer Science & Engineering Tehri India Graphic Era Hill University Dept. of Computer Science & Engineering Dehradun India Doon Group Of Institution Dept. of Computer Science & Engineering Rishikesh India THDC Institute of Hydropower Engineering and Technology Computer Science and Engineering Tehri India Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350394412

Cybersecurity safeguards computer systems, net- works, and digital information from a wide variety of cyber-attacks. Its major purpose is to protect the privacy of users' data and resources while maintaining their integrity and making them accessible in the digital world. Cybersecurity is an area that receives investment from businesses, individuals, and governments all around the world in order to secure sensitive information, key infrastructure, and digital assets. Protection of Sensitive Information Both individuals and businesses store huge amounts of sensitive information digitally, including personal data, financial records, intellectual property, and trade secrets. This information must be protected in order to prevent unauthorized access or disclosure. The protection provided by cybersecurity prevents this information from being stolen, exposed, or accessed without authorization. Cyberattacks can result in severe financial losses, including theft of funds, fraud, and the expenditures associated with recovering from a cyber incident. It is possible to prevent these types of losses by taking preventative measures. Implementing these strategies helps prevent losses of this nature. In this paper, we propose a system architecture of a generic secure system, which can be deployed for various applications, i.e., smart healthcare, Intelligent Transport Systems (ITS), smart city, etc. We discuss the threats and attacks in cyberspace. Then, we explain the requirements of cybersecurity. Further, we discuss the devastation in the absence of cyber security. We also explain the cybersecurity deployments and techniques under cybersecurity. Then, in the end, some future research directions for cybersecurity are provided. © 2024 IEEE.

关键词： Cyber attacks

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