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13th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2022

作者： Karthikeyan, G. Kousalya, G. Balakrishnan, P. Coimbatore Institute of Technology Computer Science Engineering Coimbatore India Vellore Institute of Technology School of Computer Science and Engineering Vellore India

ISBN: (纸本)9781713857938

IoT based Insulin pumps are utilized to deliver precise quantities of insulin to diabetic patients to regulate blood glucose levels. These levels correspond to the dietary patterns observed at time intervals that vary across patients. Precise representation of insulin in accordance to prescription is crucial. As such, most IoT based insulin pumps must be reinforced to endure external attacks. This includes software attacks and hardware attacks. One solution offered by the paper involves integrating Blockchain technology to ensure immutability to all instructions transmitted to the IoT Insulin pump. The second is a state-behaviour based solution that detects anomaly in the behaviour of the pump via temporal data resulting in halt of dosage. The proposed solution is successfully detects deviation in dosages ensuring safe utility. © Grenze Scientific Society, 2022.

关键词： Internet of things

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Image Captcha Blended with OTP for Secured Authentication 1

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7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Bazeer Ahamed, B. Krishnamoorthy, Murugan University of Technology and Applied Sciences College of Computing and Information Sciences Al Musannah Oman School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India

ISBN: (数字)9783031733185

ISBN: (纸本)9783031733178

With the recent development in digital currency, the number of online transactions done every day is increasing exponentially. Along with the growing need for online transactions various attacks are developed to mimic an authenticated user, one of which is a phishing attack. The effort to access important materials such as credit card particulars, usernames, and passwords for mischievous reasons. We have proposed a unified model in which image CAPTCHA serves as the input for a hashing algorithm which serves as OTP generation, to avoid phishing attacks. This system is enhanced with more attack-handling mechanisms to intensify security in online application systems with better user authentication. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Phishing

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A Machine Learning Approach to Spam Detection in Social Media Feeds 33

A Machine Learning Approach to Spam Detection in Social Medi...

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33rd IEEE International Conference on Microelectronics, MIEL 2023

作者： Sudhir, A. Joseph, L.E. Ahmad, N. Awasthi, S. Agarwal, V. Raja, S.P. Stamenkovic, Z. Vellore Institute of Technology School of Computer Science and Engineering Tamilnadu Vellore India University of Potsdam Potsdam Germany Germany

ISBN: (纸本)9798350347760

Twitter, Facebook, and Reddit are popular social networking sites for online interaction. These platforms use spam filtering techniques to identify and block spammers. However, discovering spammers is challenging in Online Social Networks (OSNs). The most commonly used technique to identify spammers is classification-based supervised techniques. However, these sys- tems are subject to "data manipulation,""imbalanced datasets,""data marking,"and "spam flow"restrictions. Malicious users exploit implicit trust ties between users to spread false infor- mation, post or tweet malicious websites, and contact legitimate people without their consent. Using unlabeled URLs in a semi- supervised manner and synthetic harmful URLs produced via adversarial learning can reduce the need for labelled samples and solve the imbalance problem. The characteristics of spam users on Twitter are investigated to enhance the effectiveness of current spam detection systems. A collection of new features, more reliable and effective than previously used ones, are used to identify Twitter spammers. The suggested attributes are evaluated using well-known machine learning classification algorithms, such as Support Vector Machines (SVM), several Naive Bayesian (NB) methods, K-Nearest Neighbor (KNN), and Random Forest (RF). © 2023 IEEE.

关键词： Social networking (online)

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Embedding (K9-C9)n into Certain Necklace Graphs 7th

Embedding (K9-C9)n into Certain Necklace Graphs

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7th International Conference on Big Data and Cloud Computing Challenges, ICBCC 2022

作者： Afiya, Syeda Rajesh, M. School of Advanced Sciences Vellore Institute of Technology Tamilnadu Chennai India School of Computer Science and Engineering Vellore Institute of Technology Tamilnadu Chennai India

ISBN: (纸本)9789819910502

In parallel and distributed computing, there are practically two networks: linear networks (also called paths) and rings (also called loops). Many efficient algorithms, such as signal and image processing, were first discovered by solving algebraic problems, graphical problems and parallel implementations involving linear networks and rings. As a result, a network having both good path and cycle embedding is crucial. In this paper, using embedding method, we simulate the cartesian product of (K9-C9)n graph into certain necklace graphs. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Linear networks

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Multi-layered access control based auto tuning relational key implications in enterprise-level multi-tenancy

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Multimedia Tools and Applications 2025年第17期84卷 17805-17836页

作者： Henge, Santosh Kumar Rajakumar, R. Prasanna, P. Parivazhagan, A. Hu, Yu-Chen Chen, Wu-Lin Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation KL University AP Vaddeswaram India Centre for Automation School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering Veltech Rangarajan Dr Sagunthala R &D Institute of Science and Technology Chennai India Department of CSE Kalasalingam Academy of Research and Education Tamilnadu Krishnankoil India Department of Computer Science Xitun District Tunghai University No. 1727 Sec. 4 Boulevard Taichung City407224 Taiwan Department of Computer Science and Information Management Providence University Taichung City Taiwan

This article discusses the importance of cloud-based multi-tenancy in private–public-private secure cloud environments, which is achieved through the isolation of end-user data and resources into tenants to ensure data confidentiality and integrity. Maintaining secure access control is a complex and critical task in multi-tenant cloud environments, and researchers have proposed innovative methods for implementing security, privacy, and authenticity. However, several challenges remain. The proposed research addresses these challenges by presenting a layered approach to multi-tenancy in an enterprise-level cloud environment. The study has three main objectives: (1) to describe and analyze the complexities of enterprise-based multi-tenancy and proposed technical solutions in a tabular format;(2) to propose multi-tenant test cases across application, software, infrastructure, and network as a service environment;and (3) to present a collaborative, relational optimal key-based multi-tenancy access control model. The proposed access control model involves integrating various secure layers, such as intranet, extranet, intra-extranet, and using feasible relational optimal keys to provide secure multi-tenant access control among various tenants of single and multiple enterprises. This model provides secure data transmission by integrating various multi-layer data filters and secure blades. The layered multi-tenancy approach offers many benefits and technical feasibilities to avoid security and privacy issues in enterprise-based multi-tenant environments. The process achieved a 93% secure mapping rate to authenticate all IN and OUT data access transactions among the various multi-tenancy of similar and distinct enterprises. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Virtualization

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Epileptic Seizure Detection using XGBC with SMOTE+ENN: Epileptic Seizure Detection through ML algorithms 6

Epileptic Seizure Detection using XGBC with SMOTE+ENN: Epile...

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6th International Conference on Digital Medicine and Image Processing, DMIP 2023

作者： Nagarajan, Sangeetha Rajangam, Vijayarajan Khan, Faiz Shukla, Mridul Singh, Manas School of Computer Science Engineering Vellore Institute of Technology Chennai India Centre for Healthcare Advancement Innovation and Research Vellore Institute of Technology Chennai India School of Electronics Engineering Vellore Institute of Technology Chennai Chennai India

ISBN: (纸本)9798400709425

Epilepsy is a disorder of the brain's nervous system in which irregular brain activity results in strange behavior, sensations, and at times loss of awareness. This paper investigates various machine learning (ML) models for the classification of Epileptic Seizure (ES) from electroencephalogram signals. Five classes in the ES dataset are converted into two prominent classes using synthetic minority oversampling with edited nearest neighbor technique and the ML algorithms are experimented on the two classes of the balanced dataset. The performance analysis with the standard metrics reveals that the extreme gradient boosting classifier performs better than other ML models with 98.65% accuracy. © 2023 ACM.

关键词： Machine learning

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Fingerprint Agreement Using Enhanced Kerberos Authentication Protocol on M-Health

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computer Systems science & engineering 2022年第11期43卷 833-847页

作者： A.S.Anakath S.Ambika S.Rajakumar R.Kannadasan K.S.Sendhil Kumar School of Computing E.G.S.Pillay Engineering CollegeNagapattinam611002India Department of Computer Science and Engineering University College of Engineering AriyalurAriyalur621705India Department of Mathematics University College of Engineering AriyalurAriyalur621705India Department of Software Systems School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014India Department of IoT School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014India

Cloud computing becomes an important application development platform for processing user data with high *** providers are accustomed to providing storage centers outside the trusted location preferred by the data ***,ensuring the security and confidentiality of the data while processing in the centralized network is very *** secured key transmission between the sender and the receiver in the network is a huge challenge in managing most of the sensitive data transmission among the cloud *** are very active over the network like real authenticated user to hack the personal sensitive data,such as bank balance,health data,personal data,and confidential documents over the cloud *** this research,a secured key agreement between the sender and the receiver using Kerberos authentication protocol with fingerprint is proposed to ensure security in *** of patients are monitored using wireless sensor devices and are then transferred to the *** protocol helps in avoiding unnecessary communication of authenticated data over the cloud *** security process is a procedure with the best security in most of the authentication *** node is responsible in carrying data packets from the sender to the receiver in the cloud *** Kerberos protocol is used in trust node to ensure *** communication between the local health center and the healthcare server is ensured by using a fingerprint feature called minutiae form,which refers to the fingerprint image of both sender and *** computational and communicational cost of the proposed system is lesser when compared with other existing authentication methods.

关键词： Protocol security m-health cloud computing biometric fingerprint kerberos protocol

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Temporal Community Analysis Using Centrality Measures

Temporal Community Analysis Using Centrality Measures

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2024 IEEE Conference on engineering Informatics, ICEI 2024

作者： Rajeshkumar, Deepak Jaysankar, Pranav Yookeesh, M.R Sree Padma Chandrasekaran, Balaji Girijakumari, Smrithy Anna University College of Engineering Guindy Department of Computer Science and Engineering Chennai India Vellore Institute of Technology Sreekanatan Nair School of Computer Science and Engineering Chennai Campus Chennai India

ISBN: (纸本)9798331505776

This research explores temporal community detection to identify patterns in course grading and offerings at The University of Illinois from Spring 2010 to Spring 2020. Using a dataset that includes course grades, subject codes, instructors, and student enrolment, the study applies four community detection algorithms - Greedy Modularity, Louvain, Leiden, and Walktrap - to examine how courses group based on grading similarities over time. The data is pre-processed, split into time slices, and represented as graphs where nodes are courses and edges are weighted by cosine similarity of grading patterns. Key metrics such as modularity, community size, edge density, overlap, and persistence are used to evaluate algorithm performance. The results provide insights into the evolution of grading structures, course groupings, and instructional trends, offering a deeper understanding of the dynamics in educational data. This analysis contributes to improved decision-making in academic program development and resource allocation. © 2024 IEEE.

关键词： Resource allocation

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IoT-Enhanced Gesture Recognition System for Healthcare Applications

IoT-Enhanced Gesture Recognition System for Healthcare Appli...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Krithika, L.B. Nallakaruppan, M.K. Baza, Mohamed Badr, Mahmoud Deora, Yuvraj Singh School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India College of Charleston Deparment of Computer Science CharlestonSC United States Polytechnic Institute Department of Networks and Computer Security UticaNY12201 United States

ISBN: (纸本)9798350351408

In response to the prevalent language barriers in medical settings, this paper proposes an innovative solution leveraging gesture recognition technology. Through the integration of deep learning models and Internet of Things (IoT) tools, the system aims to facilitate seamless communication between patients and healthcare providers. Initially, a deep learning model is developed using a personalized dataset containing various medical gestures, allowing for the recognition of nuanced patient expressions such as 'I have Fever' or 'Shoulder pain.' Additionally, the system incorporates IoT sensors to monitor vital signs like body temperature and pulse in real-time, ensuring comprehensive patient assessment. With the capability to continuously evolve and adapt to new gestures, this solution not only enhances accessibility but also improves the quality of healthcare delivery, particularly in underserved communities. By bridging the gap between language barriers and medical communication, this innovative approach holds promise for fostering inclusive and effective healthcare practices worldwide. In addressing the challenges posed by language barriers in medical interactions, this paper presents a comprehensive solution that combines gesture recognition technology with deep learning models and IoT devices. By capturing and interpreting patient gestures, such as indicating specific symptoms or discomfort, the system facilitates clear communication between patients and doctors. Furthermore, the integration of IoT sensors enables continuous monitoring of vital signs, allowing for timely interventions and personalized care. With its ability to adapt and expand to accommodate new gestures and medical scenarios, this solution represents a significant advancement in healthcare accessibility and quality. By leveraging cutting-edge technology, this approach has the potential to revolutionize healthcare delivery, particularly in areas with limited access to linguistic resources or medi

关键词： Gesture recognition

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Suicidal Prediction Using Video, Audio, and Text Analysis 2

Suicidal Prediction Using Video, Audio, and Text Analysis

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2nd International Conference on Interdisciplinary Cyber Physical Systems, ICPS 2022

作者： Chordia, Gagan Mehta, Yash Nayan, S. Soni, Harshit Gupta, Aayush Jayakumar, K. Vellore Institute of Technology School of Computer Science and Engineering Vellore India

ISBN: (数字)9781665470223

ISBN: (纸本)9781665470223

In today's society, suicide has evolved into a legitimate social medical issue. Suicidal ideation refers to people's plans to commit suicide. Suicide ideas and attempts can be triggered by a variety of factors, including long-term exposure to negative emotions or life events. Early detection of suicidal ideation is possibly the most effective method of suicide prevention of all. People can share their sufferings and sentiments in real-time thanks to developments in internet communication and interpersonal connection benefits, which provides a source for suicide thought identification. Suicide has a variety of causes, and suicidal variables vary from person to person. © 2022 IEEE.

关键词： Speech recognition

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