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2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Karthikeyan, S. Muthukumaravel, A. Department of Computer Applications Bharath Institute of Higher Education and Research Chennai India Department of Arts and Science Bharath Institute of Higher Education and Research Chennai India

ISBN: (纸本)9798331504960

The development of precise prediction models for early intervention is of the utmost importance due to the significant public health issue of the increasing prevalence of adult obesity. The study introduces an innovative approach for adult obesity prediction using deep learning and ensemble classification techniques. The current proposed approach is trying to overcome previous approaches in terms of robustness and accuracy. Normally, the proposed method is improving the prediction in performance by collecting various classifiers into one framework based on deep learning. Several classifiers are considered here, such as decision trees, SVMs, k-nearest neighbors. The system employs dynamic weighting modification scheme that optimizes input from every classifier within the training phase. On such a large dataset, experiments indicate that the proposed model is much more reliable and accurate compared to standard single-model methods for adult obesity prediction. These results showed that public health professionals may benefit from the ensemble learning that improves obesity prediction with a potential accuracy of 86.7% in monitoring populations and responding promptly, when necessary. © 2024 IEEE.

关键词： Prediction models

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Group security using ECC

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International Journal of Information Technology (Singapore) 2022年第2期14卷 955-963页

作者： Sethi, Purna Chandra Sahu, Neelima Behera, Prafulla Kumar Department of Computer Science Rama Devi Women’s University Odisha Bhubaneswar India Department of Computer Science and Applications Utkal University Odisha Bhubaneswar India

Nowadays security is main issue during transmission of data. Among many cryptographic methods, ECC is the public key asymmetric cryptosystem which provides faster computation over smaller size in comparison to other asymmetric key cryptosystems. In this paper, we have proposed a group security algorithm using the ECC cryptography algorithm. The group security is applied to ECC in terms of m-gram selection called ECC m-gram selection. Due to the group security implementation in terms of common grams, processing speed will be faster in comparison to individual item security. We have also made the comparison study between the traditional ECC algorithm with the proposed group security algorithm using generalized frequent-common gram selection for depicting lesser time requirements to achieve better security for the whole process. © 2021, Bharati Vidyapeeth's Institute of computer applications and Management.

关键词： ECC EMS GFGS Group security m-gram

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PODX: A Comprehensive Framework for Detecting Prohibited Items in Security X-Rays 9

PODX: A Comprehensive Framework for Detecting Prohibited Ite...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Shivane, Ashwini S. Bhoite, Sachin Indira College Of Commerce & Science Tathawade Pune India Dr. Vishwanath Karad Mit World Peace University Department Of Computer Science & Applications Pune India

ISBN: (纸本)9798350377972

The increasing need for accurate and reliable detection of prohibited items such as guns, knives, and pliers in X-ray security images underscores the importance of advanced frameworks to enhance security screening processes. This study introduces Prohibited Object Detection in X-rays (PODX), a comprehensive two-stage framework aimed at improving detection capabilities through advanced feature extraction and classification techniques. The framework employs a two-stage approach: in the first stage, three convolutional neural network (CNN) architectures-ResNet, GoogLeNet, and DenseNet-are utilized to extract features, which are further refined using LASSO (Least Absolute Shrinkage and Selection Operator) regression to select the most significant features for classification. In the second stage, multiple machine learning algorithms, including Random Forests, Gradient Boosting, Support Vector Machines (SVM), and K-Nearest Neighbors (KNN), are implemented to classify prohibited items based on the refined features. The performance of these algorithms is evaluated using metrics such as train accuracy and test accuracy, providing a comprehensive assessment of their strengths and weaknesses. The PODX framework not only enhances the accuracy and reliability of detecting prohibited items in security applications but also offers valuable insights into the comparative effectiveness of various classification techniques in X-ray image analysis. © 2024 IEEE.

关键词： Random forests

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Evolution of Signcryption based cryptosystem in 5G communication technologies using Design Thinking 4

Evolution of Signcryption based cryptosystem in 5G communica...

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4th International Conference on Computation, Automation and Knowledge Management, ICCAKM 2023

作者： Gavaskar, A. Sumithra Vijayalakshmi, N. Gavaskar, S. Saranya, A. Kiruthika, R. SNS College of Technology Department of Computer Science and Engineeering Coimbatore India Bharathiyar University D Department of Computer Science and Engineeering Coimbatore India Rajeswari College of Arts and Science for Women Department of Computer Applications Puducherry India SNS College of Technology Department of Electronics and Communication Engineeering Coimbatore India

ISBN: (纸本)9798350393248

With the evolution of communication technologies, various substantial applications help the human community. Various real-time applications rely on the 5G era to fulfil the baseline service requirements. These 5G network communications deploy different cryptosystems to handle the security issues between homogeneous and heterogeneous systems. Here, a novel signcryption scheme is proposed over various public cryptosystems to secure communication among the 5G network model. The anticipated model establishes mutual communication among the certificate-less public key infra-structure environment. The proposed scheme works well against the chosen adaptive ciphertext attack under various computational random problems. A bilinear pairing-based signcryption (BPS) method is proposed and executed over the MATLAB 2020a simulation environment. This model is secure over the random model and establishes a better security trade-off among the prevailing approaches. Moreover, this model analyses and quantifies the scheme's performance with metrics like time comparison over a key generation, signcryption and unsigncryption. Therefore, the model attains superior security and efficiency. © 2023 IEEE.

关键词： 5G mobile communication systems

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Dual Mode Host-Based and Cloud-Based Smartphone Intrusion Detection System 1

Dual Mode Host-Based and Cloud-Based Smartphone Intrusion De...

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1st International Conference on Futuristic Technologies, INCOFT 2022

作者： Gopala, B. Hanumanthappa, M. Kumar, Manish Bangalore University Department of Computer Science and Applications Bangalore India M S Ramaiah Institute of Technology Department of Master of Computer Applications Bangalore India

ISBN: (纸本)9781665450461

Smartphones are one of the most important devices in our daily life. It produces transfers and stores a significant amount of data about individuals such as banking transactions, authentication credentials, location details, call logs, etc. If the security of smartphones is compromised, it can severely affect the individual's life. As a result, the security system must be both efficient and dependable. We present a novel dual-mode Intrusion Detection System (IDS) that can operate both offline (without internet) and online (cloud mode). It collects application run-time data and analyses it locally on a smartphone or in the cloud, based on the user's configuration, to predict the app's behaviors and detect any intrusion. © 2022 IEEE.

关键词： Smartphones

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Double Encryption Technique for Sharing and Storing the Images in the Cloud Environment 4

Double Encryption Technique for Sharing and Storing the Imag...

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4th International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Anusha, P. Maruthi, R. Kumar, D. Maghesh Begum, H. Parveen Periyar Maniammai Institute of Science and Technology Department of Software Engineering Tamil Nadu Thanjavur India Hindustan Institute of Technology and Science Department of Computer Applications Tamil Nadu Chennai India

ISBN: (纸本)9798350343670

Cryptography is used by all organizations to protect the data files and ensures confidentiality mainly at the time of sharing and storing in the cloud data storage. The cloud service providers use a wide range of tools and techniques for encryption and storage technologies. The intruders are finding number of ways to break or attack the cryptographic systems, so that new ways are constantly being explored to safeguard our files from the attackers This paper explores double encryption cryptographic technique based on Elliptic curve cryptography (ECC) and Advanced Encryption Standard (AES) to perform end-to end encryption for sharing and storing files in the cloud environment. © 2024 IEEE.

关键词： Advanced Encryption Standard Cloud Cryptography Elliptic Curve Cryptography File Sharing

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Analysing of diverse Stress pattern in ECG using Machine Learning Techniques 2

Analysing of diverse Stress pattern in ECG using Machine Lea...

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2nd International Conference on computer Vision and Internet of Things, ICCVIoT 2024

作者： Anbarasi, S. Dhanalakshmi, B. Department of Computer Applications BS Abdur Rahman Crescent Institute of Science and Technology GST Road vandalur Tamil Nadu Chennai India Department of Computer Science and Engineering BS Abdur Rahman Crescent Institute of Science and Technology GST Road vandalur Tamil Nadu Chennai India

ISBN: (数字)9781837242535

ISBN: (纸本)9781837242672

ECG signals are commonly used to diagnose various cardiac conditions, and the classification of these signals is an important task in Stress identification. With the advancement of ML techniques, several ML models have been developed to classify ECG signals with high accuracy. This paper aims to review recent studies that use ML models for ECG classification, equivalence to the working nature of different prototype, and discuss the challenges and limitations of these models. The study found that deep learning models, such as CNNs and RNNs, outperformed traditional ML models in terms of closeness and validity. The results also showed that the combination of multiple models could improve the classification performance. However, the study also highlighted the need for large annotated ECG datasets and the requirement of domain expertise for feature engineering. Overall, this review provides a complete analysis of the current state of ECG classification using ML models and identifies areas for future research and improvement. Even though the accuracy of ML models in ECG classification is not always perfect, they can still provide valuable information and support to healthcare professionals. In some cases, even a lower accuracy can still be useful, especially in the context of large-scale screening and monitoring programs, where the goal is to identify individuals who require further evaluation. In these cases, the high computational speed and scalability of ML models make them an attractive option, as they can quickly process large amounts of data and provide preliminary results that can be followed up with more comprehensive and accurate tests. Additionally, the results from ML models can also be used as a starting point for further analysis by healthcare professionals, who can use their domain knowledge to interpret the results and make informed decisions. Therefore, despite their limitations, ML models can still play an vital role in the field of Electrocardiogram cla

关键词： Convolutional neural networks

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A 2 GHz High-Performance Design of Braun Multiplier with Hybrid Full Adder for ALU 2

A 2 GHz High-Performance Design of Braun Multiplier with Hyb...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Sakthimohan, M. Sundravadivelu, K. Amuthaguka, D. Tamil Selvan, S. Elizabeth Rani, G. Rahul, Dudekula KalaignarKarunanidhi Institute of Technology Department of ECE Tamilnadu Coimbatore India Madurai Kamaraj University Department of Computer Science Tamilnadu Madurai India Kalasalingam Academy of Research and Education Department of Computer Applications Tamilnadu Krishnankoil India Tamilnadu Coimbatore India

ISBN: (纸本)9798350365269

For applications of signal processing that are both economical and computationally intensive, efficient arithmetic circuits are required. High-reliability and portable circuits are required for electronic appliances including pagers, laptops, and notebook computers. Power dissipation has grown in relevance with the introduction of high-performance chips for effective chip design. To achieve high throughput and low power dissipation, it is now more important than ever to investigate efficient design methodologies. In the past few years, high-performance VLSI design has become more and more dependent on low power and fast circuits. An Adder and a Multiplier are the basic components of an Arithmetic & Logic Unit (ALU). An adder, is an essential unit of every ALU, performs the addition function. And a multiplier is created using this adder as a foundational element. Thus, any DSP application such as FFT or others must use multiplication as a fundamental building block. Subsequently, new strategies for planning arithmetic circuits are expected to come from the results that are wanted concerning area, power, and time. The significant objective is to make a high-performance adder and Multiplier that can work at a clock recurrence of 2 GHz. Pass transistors, transmission gates, and traditional correlative metal oxide semiconductors are utilized in the design of the proposed hybrid full adder. The aforementioned adder has been used to construct the Braun multiplier architecture for multiplication operations. Additionally, it is computed how much power and propagation delay each circuit dissipates on average. And Synopsis - PrimeSim Tool was used to complete the entire design. Our proposed system Braun Multiplier with Hybrid Full Adder achieved a very significant reduction in delay, by 80%. This translates to a potential operating frequency of around 6.7 GHz. © 2024 IEEE.

关键词： Adders

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Blockchain based Secure Erlang Server for Request based Group Communication over XMPP

Blockchain based Secure Erlang Server for Request based Grou...

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2023 International Conference on Advances in Intelligent Computing and applications, AICAPS 2023

作者： Johnpaul, C.I. Vivekanandan, Manojkumar Premkamal, Praveen Kumar Ramya, R. St. Thomas College Department of Computer Science and Applications Kerala Thrissur India Srm University-AP School of Engineering and Applied Sciences Department of Computer Science and Engineering Andhra Pradesh Amaravati India Kamaraj College of Engineering and Technology Department of Computer Science and Engineering Virudhunagar India

ISBN: (纸本)9798350333817

Many real world activities in computer science scenarios are linked with concurrency and security related issues and have to handle large number of processes to be executed in parallel with false safe security solutions. There are many traditional methods in programming languages to handle concurrency. Concurrency is one of the major issues that need to be addressed by most of the servers when dealing with the group communication operations. Security of the data as well as the credibility of the users are the other aspects when a group of users involve in real-time communication. Many light-weighted servers are designed to carryout elementary operations of request handling, file sharing etc. In design of such servers having large number of clients, the request service handling will be based on the individual server programs. Keeping track of individual credibility and establishing concurrency solutions in server design is challenging. The whole work describes the significance and implementation of an Erlang based XMPP server in comparison with a Python based XMPP server with a view to service the client request handling operations for sending messages, group chatting, buddy-list creation, presence identification integrated with XML messaging pattern as per the XMPP protocol. We also accomplish the security and credibility of the users using a blockchain based interface that keep track of user activities during group communication. The security analysis is also performed for blockchain based interface. © 2023 IEEE.

关键词： Python

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Enhancing the Compressed Video Quality through a Neural Network Approach 4

Enhancing the Compressed Video Quality through a Neural Netw...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Panneerselvam, Karthick Rajalakshmi, K. Sornalatha, P. Kpr Institute of Engineering and Technology Department of Computer Science & Engineering Tamil Nadu Uthupalayam641407 India Cmr Institute of Technology Department of Mca Karnataka Bengaluru560037 India Alagappa University Department of Computer Applications Tamil Nadu Karaikudi630003 India

ISBN: (纸本)9798331523923

Video compression mainly focuses on reducing the file size of videos with little loss of quality, but most video compression algorithms on the market do not focus on clarity. Data compression is increasingly being considered as a necessary issue in larger engineering communities. Data compression using neural networks has been the main topic of some related research. The main objective of this study would be to apply the video in an amazing way with the help of an Enhanced Generative Adversarial Network (EGAN). EGAN was better to manage and produced better consistent results with fewer artifacts than other Neural Networks (NN). Deep neural networks (DNNs), recurrent neural networks (RNNs), generational adversarial networks (GANs), and various autoencoder (AE) variants have all been used for various compression methods. It would be a potential option for incredible movies. Based on significantly reduced sample input films, the proposed neural network was able to maintain high-frequency information and generate pleasurable sensory videos. A Residual Dense Block (RDB) is the sort of block utilized in the design. In comparison to previous state-of-the-art approaches, the comprehensive Mean-Opinion-Score (MOS) test, and the Video Multi-Method Assessment Fusion (VMMAF) test, reveal extremely substantial increases in terms of human experiential accuracy. The researchers are also proposing a new data pre-processing method based on the Deep Recurrent Neural Network (DRNN) that has been combined with two leading-edge coding standards, and the Adaptable Video Coding (AVC). The results show consistent encoding benefits across all sequences examined at multiple spatial frequencies, with an average bit rate savings of 4.0 percent relative to AVC. © 2025 IEEE.

关键词： Image coding

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