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2024 International Conference on Communication, Computing and Energy Efficient Technologies, I3CEET 2024

作者： Sneha, Kandi Shareef, Khaja Mohammad Fazil Afzal Sri, Marumanula Bhanu Moses, Kolli Manish Geetha, G. B V Raju Institute of Technology Dept. Computer Science Engineering Narasapur Telangana Medak District502313 India

ISBN: (纸本)9798331541583

Due to the exponential rise in electronic transactions, credit card theft is becoming a major concern for both consumers and financial institutions. The goal of this research is to create a sophisticated fraud detection system that leverages machine learning techniques. A large dataset that includes transaction details, user activities, and historical patterns is used by the suggested system. The model seeks to precisely identify and categorize fraudulent behaviors in real-time by utilizing supervised learning approaches, such as Random Forest, Support Vector Machines, and Neural Networks. In order to assess the model's effectiveness in reducing false positives and false negatives, it is benchmarked against current fraud detection techniques. The results of this study support continuing efforts to strengthen financial systems against fraudulent activity, so improving © 2024 IEEE.

关键词： Support vector regression

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Application to Enhance the Programming Knowledge of Children

Application to Enhance the Programming Knowledge of Children

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Advancements in Computing (ICAC), International Conference on

作者： Anuga Dissanayake Vishwa Lakpriya Mahendran Sanjeevan Ahamed Fahmi Samanthi E.R. Siriwardana Mihiri Samaraweera Dept. of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Dept. of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331517878

ISBN: (纸本)9798331517885

This proposal outlines the development of a comprehensive educational platform aimed at bridging the Information technology knowledge gap among Tamil-speaking students in Sri Lanka. The platform is designed to enhance programming skills through personalized quizzes, hands-on projects, and adaptive learning models. The application focuses on two primary components: the first component emphasizes project-based learning and assessments, leveraging advanced Artificial Intelligence models for generating educational content. This model is combined with Retrieval-Augmented Generation, which retrieves relevant external information to refine and tailor the educational content to each student's needs. This component keeps students engaged and challenged at appropriate levels, promoting deeper understanding and practical Information technology skills. The second component involves a Level-based IT Fundamental Knowledge Evaluation system, which incorporates machine learning algorithms to predict student performance, recommend customized learning paths, and assess overall technical knowledge. The platform also integrates the OpenAI Application Programming Interface, which provides real-time Tamil translation, making the content more accessible to the target demographic. The platform empowers educators to better address individual student needs with real-time feedback and tailored experiences. Its innovative approach enhances Information technology education, equipping Sri Lankan students with essential programming skills to succeed globally.

关键词： Adaptation models Translation Machine learning algorithms Computational modeling Retrieval augmented generation Learning (artificial intelligence) Real-time systems Proposals Information technology Programming profession

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A Secure Token-Based Approach for DHCP Client Authentication and Replay Attack Prevention

A Secure Token-Based Approach for DHCP Client Authentication...

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International Conference on computer and Information technology (ICCIT)

作者： Asaduzzaman Jony Muhammad Nazrul Islam Rahat Ahmed Talukder Dept. of Information and Communication Technology Bangladesh University of Professionals (BUP) Dhaka Bangladesh Dept. of Computer Science and Engineering Military Institute of Science and Technology (MIST) Dhaka Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

Dynamic Host Configuration Protocol (DHCP) plays a crucial role for assigning IP address and other related parameters to clients. Due to lack of client authentication and anti reply mechanism the DHCP protocol is susceptible to DHCP starvation attack. Although most of the existing researches proposed digital certificate based DHCP client authentication that involves a trusted third party named certificate authority (CA), but securing the private key of certificate authority is very challenging and risky task. Again, traditional MAC binding technique has been used to authenticate DHCP clients which could be easily evaded by MAC spoofing attack. Moreover, SMS based one time password (OTP) is also suggested to authenticate DHCP clients which is susceptible to Man-In-the-Middle (MITM) attack as OTP is transmitted in plain text. Therefore, the objective of this research is to propose an effective DHCP framework to authenticate DHCP clients and prevent DHCP replay attack. To achieve this objective, at first, DHCP starvation and DHCP replay attack and their consequences are briefly demonstrated. Secondly, a python-based secured DHCP framework was proposed that authenticates DHCP clients and prevents DHCP replay attack by exchanging security tokens uniquely generated from clients Pre-Shared Key (PSK), MAC address, PIN and system time. Finally, the effectiveness and validation of the proposed DHCP framework is demonstrated using the Multivendor Network Emulation Software (EVE-NG).

关键词： Phase shift keying Protocols Prevention and mitigation Authentication Public key Production Passwords Software Pins Servers

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EAI Endorsed Transactions: AI Research 3

EAI Endorsed Transactions: AI Research

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3rd IEEE International Conference on Interdisciplinary Approaches in technology and Management for Social Innovation, IATMSI 2025

作者： Karad, Sachin Chandravadan Singh, Balpreet Krishna, Gopal Ambhika, C. Yadav, Kanchan Sikarwar, Shailendra Singh Lovely Professional University Dept. of Electronics and Electrical Engineering Punjab India Uttaranchal University Uttaranchal Institute of Technology Dehradun India R.M.D Engineering College Dept. of Aiml Jharkhand India Gla University Dept. of Computer Eng. & Applications Mathura India Jiwaji University Dept. of Cs Gwalior India

ISBN: (纸本)9798331521691

This research provides a thorough review of wearable health monitoring devices and explores their potential in managing individual health. The study emphasizes how wearables can assist in early detection of health issues and empower users to take control of their well-being. It also examines the application of various machine learning algorithms to determine the most suitable approach for different situations. The report suggests that incorporating artificial intelligence in the future could lead to more personalized health insights. Additionally, it stresses the need for continued research to enhance the impact of wearable health monitoring devices on individual health and wellness. The objective of this study is to evaluate the effectiveness of Random Forest, KNN, and Logistic Regression in health monitoring systems. The study compares these algorithms to draw clear conclusions on their suitability and examines how each handles the challenges of high-dimensional health data commonly encountered in monitoring systems. To ensure data quality, the study selects several health monitoring datasets and processes them accordingly. Performance metrics are used to evaluate the execution of the Random Forest, KNN, and Logistic Regression algorithms. The study analyzes how well each algorithm deals with high-dimensional data issues and assesses its ability to deliver clear, actionable insights. While the effectiveness of these algorithms can be improved through parameter tuning, resilience is ensured through cross-validation. Strengths and weaknesses are identified through statistical testing and comparison, with results presented for clarity. The study also addresses the limitations, challenges, and recommendations for selecting the best algorithm for health monitoring systems. © 2025 IEEE.

关键词： Artificial Intelligence KNN Wearables

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Protecting Sensitive Data in the Cloud: A Network Security Approach 15

Protecting Sensitive Data in the Cloud: A Network Security A...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Mohammed, Abdul Sajid Sreeramulu, Madhusudhan Dasari Gopal, Santhosh Kumar Gupta, Ketan Anand Kumar, V. University of the Cumberlands Dept of School of Computer and Information Sciences KY United States American Express Dept of Cyber Security United States Charlotte NC United States University of The Cumberlands Dept. of Information Technology WilliamsburgKY United States Sri Eshwar College of Engineering Department of Ece Tamil Nadu Coimbatore641202 India

ISBN: (纸本)9798350370249

Cloud Computing adoption has increased dramatically over the past few years, making the protection of sensitive data on the cloud a major concern. In this paper network security is presented as an effective way to ensure the security of data on the cloud using methods like encryption, access control, and DLP. The method concentrates on the security of the network infrastructure, and also the internal cloud environment security controls. This methodology combines internal and external security measures to provide an overall protection of data housed in the cloud. Conclusions The work is mainly intended to increase the understanding of the need for network security and shielding data in the cloud, and someways to enhance data security in the cloud for businesses and organizations. © 2024 IEEE.

关键词： Cloud Computing Data Privacy Encryption Network Security Protection

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NB-IoT Preamble Signal: A Survey 7

NB-IoT Preamble Signal: A Survey

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7th IEEE World Forum on Internet of Things, WF-IoT 2021

作者： DIan, F. John Vahidnia, R. British Columbia Institute of Technology Dept. of Electrical and Computer Engineering Burnaby Canada

ISBN: (纸本)9781665444316

The Narrowband Internet of Things (NB-IoT) is a cellular IoT communication technology to address the IoT use cases where the smart devices can establish a connection with the network using Random Access (RA) process. The RA process begins with sending a preamble signal in uplink direction. In this paper, we explain about this signal and discuss the effect of wireless channel on the preamble signal. We model the preamble signal at the transmitter side as well as the receiver side. We also classify the research work performed on this signal to four different clusters and consequently explain the methods and techniques utilized in each cluster. © 2021 IEEE.

关键词： Internet of things

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Cryptography and Adversarial Analysis for Cloud Data Security

Cryptography and Adversarial Analysis for Cloud Data Securit...

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Innovative Trends in Information technology (ICITIIT), International Conference on

作者： S. Manjula K. Valarmathi M.Swarna Sudha Dept. of Computer Science and Engineering Ramco Institute of Technology Rajapalayam Tamil Nadu India Dept of Electronics and Communication Engineering P.S.R Engineering College Sivakasi Tamil Nadu India

ISBN: (数字)9798350386813

ISBN: (纸本)9798350386820

Cloud computing, a novel paradigm for distributed data processing, has emerged as a transformative technology enabling the storage and retrieval of data over the Internet. The prevalence of Software-as-a-Service has revolutionized work dynamics, fostering a culture of secure remote access across diverse devices. Within the realm of Cloud Storage, the imperative for effective security and privacy measures is underscored. This research proposes a robust data security framework employing the Cryptography Splitting Algorithm. User files undergo encryption, increasing security levels from 25 to 75 are securely stored with a cloud service provider. The Cloud Manager empowers users by enhancing security, managing tracking mechanisms, and safeguarding metadata, thus fortifying data confidentiality and flexibility in utilization. Leveraging the Cryptography Splitting technique ensures secure data storage, concurrently enhancing both security and privacy for user data. Furthermore, the proposed methodology undergoes rigorous scrutiny in an adversary setup, incorporating neural network analysis to evaluate the resilience of data security measures. This analysis reveals the encryption scheme protects communication by maintaining a low $A-B$ loss around 0.1 while reducing Eve’s ability to intercept messages from 0.7 to 0.2. This research contributes a comprehensive approach to securely managing data in the dynamic landscape of cloud computing.

关键词： Cloud computing Data privacy Privacy Heuristic algorithms Neural networks Software as a service Encryption

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Trustworthy Text-to-Image Diffusion Models: A Timely and Focused Survey

arXiv

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arXiv 2024年

作者： Zhang, Yi Chen, Zhen Cheng, Chih-Hong Ruan, Wenjie Huang, Xiaowei Zhao, Dezong Flynn, David Khastgir, Siddartha Zhao, Xingyu WMG The University of Warwick United Kingdom The Dept. of Computer Science University of Liverpool United Kingdom The Dept. of Computer Science & Engineering Chalmers University of Technology Sweden The James-Watt Engineering School University of Glasgow United Kingdom

Text-to-Image (T2I) Diffusion Models (DMs) have garnered widespread attention for their impressive advancements in image generation. However, their growing popularity has raised ethical and social concerns related to key non-functional properties of trustworthiness, such as robustness, fairness, security, privacy, factuality, and explainability, similar to those in traditional deep learning (DL) tasks. Conventional approaches for studying trustworthiness in DL tasks often fall short due to the unique characteristics of T2I DMs, e.g., the multi-modal nature. Given the challenge, recent efforts have been made to develop new methods for investigating trustworthiness in T2I DMs via various means, including falsification, enhancement, verification & validation and assessment. However, there is a notable lack of in-depth analysis concerning those non-functional properties and means. In this survey, we provide a timely and focused review of the literature on trustworthy T2I DMs, covering a concise-structured taxonomy from the perspectives of property, means, benchmarks and applications. Our review begins with an introduction to essential preliminaries of T2I DMs, and then we summarise key definitions/metrics specific to T2I tasks and analyses the means proposed in recent literature based on these definitions/metrics. Additionally, we review benchmarks and domain applications of T2I DMs. Finally, we highlight the gaps in current research, discuss the limitations of existing methods, and propose future research directions to advance the development of trustworthy T2I DMs. Furthermore, we keep up-to-date updates in this field to track the latest developments and maintain our GitHub repository at: https://***/wellzline/Trustworthy_T2I_DMs. © 2024, CC BY.

关键词： Economic and social effects

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Semantic-Aided Image Transmission System with Unequal Error Protection for Next-Generation Communication Networks

Semantic-Aided Image Transmission System with Unequal Error ...

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IEEE Conference on Wireless Communications and Networking

作者： Nargis Fayaz Aman Shreshtha Smruti Sarangi Ranjan K. Mallik Brejesh Lall Dept. of Electrical Engineering Indian Institute of Technology Delhi New Delhi India Dept. of Computer Science and Engg Indian Institute of Technology Delhi New Delhi India

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

Semantic communication (SC) aims to convey the meaning of data instead of focusing on its bit-by-bit reconstruction. SC finds applications in beyond 5G and 6G networks for artificial intelligence-empowered multimedia content delivery. In this paper, we propose a novel semantic-aided autoencoder-based image transmission system that leverages semantic information in the form of the segmentation map of an image. We demonstrate up to 23% and 18% improvement (in terms of mean square error and peak signal-to-noise ratio, respectively) in the quality of the received image with only 2% extra bandwidth over a traditional autoencoder-based image transmission system. The study also explores channel coding strategies for our proposed system. We focus on the intrinsically robust nature of semantic data, as compared to traditional data, to design low-density parity check code, Hamming code, and polar code-based unequal error protection (UEP) schemes. Comparative evaluations between UEP and equal error protection schemes show that while both approaches yield similar performance, UEP schemes are more efficient.

关键词： Image segmentation PSNR Image communication Semantics Bandwidth Syntactics Parity check codes

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CAs Based Student-Alumni Management System

CAs Based Student-Alumni Management System

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2021 International Conference on Communication, Control and Information Sciences, ICCISc 2021

作者： Nishanth, D.V. Satish Narasimha, Niteesh S. Sandesh, H.J. Bhargavi, K. Siddaganga Institute of Technology Dept. of Computer Science and Engineering TumakuruKarnataka India

ISBN: (纸本)9781665412797

Students and alumni management system of any university is a collaborative framework which integrates the knowledge between the students who are pursuing education and the students who have already successfully established themselves after graduation. There are various profession choices that are available wherein a person could choose from and this proposed framework is a predictive system which tries to predict the career option based on the success rate of the student in terms of his credentials CGPA, number of projects, number of publication, and so on and the credentials of the alumni like number of years of experience, proprietorship, number of recognitions, designation reached, and many more. The proposed system tries to collaborate students with alumni or the ones who have graduated out of the university and together they are provided an option to choose their career based on all the experiences they have had so far and the necessary credentials they own. Cognitive-Agents (CAs) which exhibits rational thinking which is applied in the paper to collaborate the students and alumni where in the beliefs over the students and alumni are formulated using the Behaviour-Observation-Belief (BOB) model. The performance achieved by the proposed CAs based framework towards alumni management in university is found to be good with respect to parameters like employment rate, student alumni association, and so on. © 2021 IEEE.

关键词： Students

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