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2024 International Conference on Innovation and Intelligence for informatics, Computing, and Technologies, 3ICT 2024

作者： Kalyani, G. Jayaraman, Venkatesh Sathish Kumar, P.J. Surendran, R. Balamurugan, K.S. Karpaga Vinayaga College of Engineering and Technology Tamil Nadu Chengalpattu India Department of Computer Science and Engineering Chennai Institute of Technology Chennai India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Electronics and Communication Engineering Karpaga Vinayaga College of Engineering and Technology Tamil Nadu Chengalpattu India

ISBN: (纸本)9798331533137

This study proposes a unique sensor plus machine learning system designed to enhance patient care and targeted medicine administration, with a specific focus on controlling Cryptococcosis, in the search for more precise and proactive healthcare solutions. This research had contributed to the conceptualization, design and implementation of system which integrates constant sensor data monitoring and machine learning algorithms to anticipate and prepare for any health problems. Over the course of a day, Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Random Forest (RF) were used to analyse sensor data from 10 patients with Cryptococcosis. The sensor data gathered from these people included information on their body temperature, blood pressure, oxygen saturation, heart rate, blood sugar levels, and ECG measurements. The models executed flawlessly, achieving F1 scores for accuracy, recall, and precision. SVM won with a precision score of 97.6%, followed by ANN with a score of 95.3% and RF with a score of 92.1%. The models' capacity to get rid of misclassifications and provide precise predictions needed for right away action was demonstrated by the confusion matrices that went along with them. This discovery, which might revolutionise how patients are treated for difficult-to-treat illnesses like cryptococcosis, is an encouraging first step in the direction of proactive healthcare management. The sensor and machine learning system offers a patient-centered, data-driven approach that keeps up with the changing landscape of healthcare. ©2024 IEEE.

关键词： Support vector machines

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Smart Chatbot for College Information Enquiry Using Deep Neural Network 9

Smart Chatbot for College Information Enquiry Using Deep Neu...

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9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Channabasamma Lakshmi Soumya, P. Indu, Mukkari Swetha, Nooka Saritha, Chennuri Gokaraju Rangaraju Institute of Engineering and Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350397376

website and assist with navigation to a certain location inside the college. Information about the college, the administration, departments, activities, etc. is available on the GRIET (Gokaraju Rangaraju institute of engineering and technology) website. It gives parents and students the information that requires. Instead of visiting the college for each inquiry, a chatbot application that enables students and parents to obtain information about the institution may simply resolve the issue online, saving a great deal. Using the flask framework, the chatbot model is coupled to the HTML (Hyper Text Markup Language) and CSS-coded (Cascading Style Sheet) website. A deep neural network is trained using PyTorch for the chatbot model. It is instructed on all of the frequently asked questions and typical queries. The chatbot is available at any time where parents and students can get the information. The navigator provides directions to an individual to the desired locations effortlessly in GRIET Organization. © 2023 IEEE.

关键词： Deep neural networks

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Privacy preserving data mining – past and present

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International Journal of Business Intelligence and Data Mining 2022年第2期21卷 149-170页

作者： Kumar, G. Sathish Premalatha, K. Department of Computer Science and Engineering Sri Krishna College of Engineering and Technology Tamil Nadu Coimbatore India Department of Computer Science and Engineering Bannari Amman Institute of Technology Tamil Nadu Erode India

Data mining is the process of discovering patterns and correlations within the huge volume of data to forecast the outcomes. There are serious challenges occurring in data mining techniques due to privacy violation and sensitive information disclosure while providing the dataset to third parties. It is necessary to protect user’s private and sensitive data from exposure without the authorisation of data holders or providers when extracting useful information and revealing patterns from the dataset. Also, internet phishing gives more threat over the web on extensive spread of private information. Privacy preserving data mining (PPDM) is an essential for exchanging confidential information in terms of data analysis, validation, and publishing. To achieve data privacy, a number of algorithms have been designed in the data mining sector. This article delivers a broad survey on privacy preserving data mining algorithms, different datasets used in the research and analyses the techniques based on certain parameters. The survey is highlighted by identifying the outcome of each research along with its advantages and disadvantages. This survey will guide the future research in PPDM to choose the appropriate techniques for their research. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Privacy-preserving techniques

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A Novel Emotion based Music Recommendation System using CNN 7

A Novel Emotion based Music Recommendation System using CNN

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

作者： Tejaswini Priyanka, V. Reshma Reddy, Y. Vajja, Dharani Ramesh, G. Gomathy, S. Gokaraju Rangaraju Institute of Engineering and Technology Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350397253

Music has a unique emotional connection with humans. It is a means of connecting individuals from all over the world. On the other hand, it is a highly difficult task to generalize music and claim that everyone would prefer and enjoy the same type. Emotion-based music selection is important because it can assist humans in reducing stress. Its major purpose is to accurately predict the user's emotions, and play songs depending on the user's preferences. Using Human computer Interaction (HCI), the proposed bot recognizes human emotions from facial emotions. Another significant challenge is the extraction of facial features from the user's face. The proposed CNN Algorithm is utilized in the proposed model to properly capture and recognize the user's face from the live webcam stream and to detect emotions based on facial factors such as lips and eyes. Also, an additional option will be provided for people to make a good choice manually. © 2023 IEEE.

关键词： Emotion Recognition

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Fog Computing in the Internet of Things: Challenges and Opportunities 6th

Fog Computing in the Internet of Things: Challenges and Oppo...

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6th IFIP International Conference on Internet of Things, IFIP IoT 2023

作者： Shah, Iqra Amin Chishti, Mohammad Ahsan Baba, Asif I. Department of Information Technology School of Engineering and Technology Central University of Kashmir Kashmir India Department of Computer Science and Engineering National Institute of Technology Srinagar Kashmir India Department of Computer Science and Engineering University of North Texas DentonTX76207 United States

ISBN: (纸本)9783031458811

The expansion of the Internet of Things (IoT) has made it possible for numerous widespread objects to connect to one another and communicate with one another, leading to unprecedented data releases. However, regardless of the fact that cloud computing has been a useful tool for processing and storing these data, problems like the growing demand for real-time applications and the constrained availability of network bandwidth cannot yet be resolved solely through the use of cloud computing. As a supplement to the cloud solution, a new approach to computing called the fog computing paradigm has been developed. By moving processing, connectivity, and capacity nearer to edge gadgets and end clients and taking cloud computing to the network’s edge, fog computing aims to increase low latency, activity, data traffic, reliability, and privacy. The present paper discusses the framework of the fog computing model and presents a literature survey of various works that is carried out on fog computing. It also covers the current problems and difficulties in fog computing and opportunities for research in the area of Fog computing for the Internet of Things. © 2024, IFIP International Federation for Information Processing.

关键词： Fog computing

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Comparative Analysis of Different Machine Learning Algorithms on Different Datasets 7

Comparative Analysis of Different Machine Learning Algorithm...

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

作者： Raju, G. S Bapi Manasa, Chintala Bhavani, Nandikatti Durga Amulya, Jadi Shirisha, Dangatla Gokaraju Rangaraju Institute of Engineering and Technology Computer Science and Engineering Department Hyderabad India

ISBN: (纸本)9798350397253

Machine Learning is used to train models and machines without the help of any human interventions and guides. Here the models and machines are trained using algorithms. As it is difficult to train the algorithms one by one and get the analysis of the best algorithm. This research study intends to compare different algorithms used in different datasets to know the best algorithm according to different domains and the overall best algorithm. In this study, most popular supervised algorithms like SVM, Decision Tree, Random Forest, KNN, Logistic Regression, XGBoost, Adaboost, Voting Classifier (Decision Tree + Random Forest), Bagging Classifier (KNN + SVM) and Naïve Bayes. This research study has chosen three different domains for datasets. Different datasets were used to check the efficiency of algorithms. Comparative analysis of the classifiers shows that all algorithms outperform the existing methods with a high accuracy. © 2023 IEEE.

关键词： Adaptive boosting

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Real-time Face-based Gender Identification System Using Pelican Support Vector Machine 2

Real-time Face-based Gender Identification System Using Peli...

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2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Ojo, Olufemi S. Oyediran, Mayowa Oyedepo Awodoye, Olufemi O. Ajagbe, Sunday Adeola Awotunde, Joseph Bamidele Bandyopadhyay, Anjan Adigun, Matthew O. Department of Computer Science Ajayi Crowther University Oyo Nigeria Department of Computer Engineering Ajayi Crowther University Oyo Nigeria Department of Computer Engineering First Technical University Ibadan200255 Nigeria Department of Computer Science University of Ilorin Ilorin Nigeria School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India Department of Computer Science University of Zululand Kwadlangezwa3886 South Africa

Gender identification from video is an emerging research field that aims to automatically classify the gender of individuals based on video data. Due to the numerous applications for this task, it has received a lot of attention, including surveillance, human-computer interaction, and targeted marketing. In this study, we propose a gender identification system that utilizes the Pelican optimizer algorithm in combination with a Support Vector Machine (SVM) classifier. The Pelican optimizer is a metaheuristic algorithm inspired by the hunting behaviour of pelicans and has shown promising results in solving optimization problems. Pelican optimizer algorithm (POA) is applied to optimize the SVM parameter selection process such as kernel function. The POA algorithm searches for an optimal subset of parameters that maximizes the classification performance of the SVM model after the application of preprocessing and feature extraction techniques such as Local Binary Pattern (LBP). Finally, the selected optimized parameters otherwise known as POA-SVM classifier learns a decision boundary based on the labeled training data. The POA-SVM model is trained to distinguish between male and female samples and generalize the classification to unseen video data. Experimental evaluations are conducted using a benchmark dataset consisting of video samples with labelled gender information. The effectiveness of the suggested system is contrasted with other cutting-edge gender identification techniques. The results demonstrate the effectiveness of the Pelican Optimization Algorithm-SVM system, showing improved accuracy of 95%, and sensitivity of 94.4% at a faster recognition rate in gender classification from video data. © 2024 Elsevier B.V.. All rights reserved.

关键词： Support vector machines

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Delving into the Realm of Information-Theoretic Security Emerging Trends and Future Directions

Delving into the Realm of Information-Theoretic Security Eme...

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2024 International Conference on Communication, computer Sciences and engineering, IC3SE 2024

作者： Srilekha, Gopu Santosh Kumar, B. Singh, Navdeep Singh, Jay Bhavana, Munugapati Jabbar, Ahmed Sabah Abed AL-Zahra Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India New Horizon College Of Engineering Department Of Computer Science Engineering Bangalore India Lovely Professional University Phagwara India Gl Bajaj Institute Of Technology & Management U.P. Greater Noida India Mlr Institute Of Technology Department Of Computer Science And Information Technology Telangana Hyderabad India College Of Medical Technology The Islamic University Medical Laboratory Technology Department Najaf Iraq

ISBN: (纸本)9798350366846

QKD, ECC, PQC, SMPC, and biometric-based authentication are examined in this work as essential information-theoretic security approaches. Each solution improves information-theoretic security by improving communication, error reduction, quantum-resistant cryptography, project collaboration, and identity verification. Quantum Key Distribution employs quantum entanglement and regular transmission to secure key exchange in a 12-step flowchart. Error-Correcting Code Implementation employs Reed-Solomon codes to discover and rectify errors in delivered messages in 10 steps, protecting data. Post-Quantum Cryptography uses a 10-step graphic to demonstrate lattice-based solutions for post-quantum security and secure communication. A 10-step 'safe multi-party computing' procedure enables individuals to collaborate on a computer project while safeguarding their privacy. It uses homomorphic encryption to secure protected data computations. Biometric authentication employs biometric data to verify a person's name in 10 steps with complicated arithmetic. Tables and graphs indicate that the information-theoretic approach outperforms other security techniques in key size, quantum attack resistance, authentication strength, and total security. These results demonstrate that the suggested strategy may considerably increase information-theoretic security in many scenarios. The response to the developing field of information security is robust. © 2024 IEEE.

关键词： Quantum cryptography

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Personalized Method for Voting in Wireless Mobile Adhoc Networks with Intrusion Detection using NS2 Simulation Model 5

Personalized Method for Voting in Wireless Mobile Adhoc Netw...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Muthukumar, S. Senthil Pandi, S. Menaga, D. Sudhahar, T.N. St.Joseph's Institute of Technology Department of Computer Science and Engineering Tamilnadu Chennai India Rajalakshmi Engineering College Department of Computer Science and Engineering Tamilnadu Chennai India Rajalakshmi Institute of Technology Department of Artificial Intelligence and Data Science Tamilnadu Chennai India

ISBN: (纸本)9798331504403

Mobile Ad hoc Networks (MANETs) are wireless networks that are self-configuring, infrastructure-less, and dynamic. The nodes in these networks have limited access to available resources. MANETs use intrusion detection systems, also known as IDS, to monitor activities in order to identify any potential intrusions into the network, which would otherwise be vulnerable. In this study, we offer efficient techniques for maximizing the length of time that intrusion detection systems need to be active in a mobile ad hoc network and monitoring how much time they need to be active for. The dissemination of a probabilistic model that makes use of neighborhood node IDS collaboration in order to reduce the amount of individual active time. In order to monitor network activities, an IDS often needs to be running nonstop on every node. In terms of electricity and processing resources, this could end up being a costly overhead for a mobile device that runs on batteries. We therefore want to shorten the IDSs' active time in this work without sacrificing their effectiveness. We simulate the interactions between IDSs as a multiplayer cooperative game with partially cooperative and partially opposing aims in order to validate our suggested methodology. We investigate this game theoretically and provide evidence from simulations. © 2024 IEEE.

关键词： Network intrusion

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NTFS: Introduction and Analysis from Forensics Point of View 2

NTFS: Introduction and Analysis from Forensics Point of View

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2nd International Conference for Advancement in technology, ICONAT 2023

作者： Hermon, Rahul Singh, Upasna Singh, Bhupendra Defense Institute of Advanced Technology School of Computer Engineering and Mathematical Sciences Pune India Indian Institute of Information Technology Computer Science and Engineering Department Pune India

ISBN: (纸本)9781665475174

New technology File System (NTFS) is a file system being used by Windows Operating Systems since 1993. NTFS is a file system used by the Windows Operating Systems for storing, cataloguing and discovering/finding files. In this work we will learn about the basics of NTFS to include its file structure and other important attributes. Then carry out analysis of NTFS file system using WinHex and Active@ Disk Editor tools from a forensics point of view, compare the results of both tools. Lastly, we carried out comparison of NTFS in Windows 10 and 11 Operating System to include forensics analysis using WinHex and Active@ Disk Editor tools. © 2023 IEEE.

关键词： Windows operating system

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