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Enhancing wireless sensor network longevity and security: A quad-leach approach

Enhancing wireless sensor network longevity and security: A ...

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2024 IEEE International Conference on Emerging Technologies in computer science for Interdisciplinary Applications, ICETCS 2024

作者： Lohith, J.J. Shreya, S. Hamsa Priya, J.L. B.M.S. College of Engineering Dept. of Computer Science and Engineering Bangalore India D.S.C.E. Dept. of Information Science and Engineering Bangalore India B.M.S. College of Engineering Dept. of Electronics and Telecommunications Bangalore India

ISBN: (纸本)9798350372502

Researchers have increasingly focused on Wireless Sensor Networks (WSNs) in recent years, recognizing their versatile applications. The primary focus within WSNs is enhancing network longevity for efficient resource utilization, coupled with a strong emphasis on security and authentication. This paper specifically delves into the implementation of Quad LEACH for homogeneous networks, aiming to substantially improve network lifetime, stability, and throughput. The proposed protocol achieves this by employing a cluster head selection process and integrating security and authentication measures between cluster heads in the Quad-LEACH routing protocol. The research addresses the integration of a security agent within WSNs using the NS-2 tool, contributing to enhanced authentication. The implementation is carried out through the simulation software NS 2, where the security agent is seamlessly combined with the WSN infrastructure. The objective of this research is to incorporate a reliable authentication and security agent into NS-2 in conjunction with the LEACH protocol, which is the standard for wireless sensors networks (WSNs). The efficacy of the suggested methodology will be validated through simulated outcomes. © 2024 IEEE.

关键词： Wireless sensor networks

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A Time-varying Velocity Control Strategy for Balancing Exploration and Exploitation Behaviour of a Binary PSO

A Time-varying Velocity Control Strategy for Balancing Explo...

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

作者： Siddique, Md. Abu Bakkar Islam, Md. Jakirul DUET Gazipur Dept. of Computer Science and Engineering Gazipur Bangladesh

ISBN: (纸本)9798350316001

Combinatorial optimization problems (COPs) are NP-hard, and their solution space is discrete, which poses a significant challenge for optimization algorithms. Binary Particle Swarm Optimization (BPSO) is wel-known optimization technique that has been widely applied in various type of COPs. However, one of the challenges in BPSO is to balance exploration and exploitation to locate the optimal solution. This paper presents a Time-varying Velocity Control (TVC) strategy to balance exploration and exploitation in a BPSO. The TVC strategy utilizes a time-varying control parameter to adjust the velocity of the particles, allowing for more exploration in the early phases of the optimization process and more exploitation as the search progresses. The proposed strategy is evaluated on a set of benchmark combinatorial optimization problems, and the results demonstrate that it outperforms other commonly used BPSO strategies in terms of both efficiency and solution quality. Furthermore, the TVC strategy is shown to be robust to changes in the problem landscape, making it a promising approach that can be used for solving a wide range of combinatorial optimization problems. © 2023 IEEE.

关键词： Combinatorial optimization

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Multiple Disease Prediction Based on User Symptoms using Machine Learning Algorithms 2

Multiple Disease Prediction Based on User Symptoms using Mac...

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2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Pentela, Ujwala Meesala, Anjali Nirupama Karingula, Deekshitha Seelamsetti, Nandini Krishna Veerlapalli, Swapna Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350347456

Every day, many individuals encounter different illnesses. The prognosis of a disease is the most pivotal part of treatment. Enormous increase in healthcare and medical data enabled accurate medical data analysis, which aids in early sickness discovery and beforehand patient care. This study focuses on performing research on the enormous medical data by exercising numerous supervised classification algorithms like Decision Tree, Support Vector Machine, K- Nearest Neighbor, Logistic Regression, Naive Bayes and Random Forest to anticipate the most probable disease grounded on the symptoms and also to directly prognosticate the possibility of whether or not the person might be suffering from that particular illness. Based on the symptoms, the model uses the results of the supervised classification algorithms and gives a final validation indicating the disease that the existent might be suffering. On combining the prognostications from all the below classification algorithms, the model returns a more accurate verification when compared to the prognostications made by individual models. This study enhances the swiftness of decision-making and can reduce the rate of false cons. It helps healthcare associations make better decisions about how to proceed with early patient care. It also aids healthcare professionals in developing further effective ways of treating patients. © 2023 IEEE.

关键词： Support vector machines

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Efficient Cache Timing Attack on the Present Algorithm for Master Key Recovery

Efficient Cache Timing Attack on the Present Algorithm for M...

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2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

作者： Amsaprabhaa, M. Dhyaneswaran, T. Harshitha, R.S. Shiv Nadar University School of Engineering Dept. Computer Science and Engineering Chennai India

ISBN: (纸本)9798350308167

Conventional side-channel attacks have limitations, like being inefficient, facing considerable challenges in gathering and injecting fault data in real-world scenarios, and having limited practicality. In recent years, a novel form of side-channel attack called the "cache timing attack"has emerged. This technique capitalizes on the disparities in the computer CPU cache's reading speeds to allow attackers to access confidential information during algorithm execution. It offers high attack efficiency and comes with relatively low costs. The "Present"algorithm, introduced in 2007, is a lightweight block cipher with outstanding hardware implementation and a streamlined round function design. Researchers from both domestic and international backgrounds have explored various side-channel attack methods on this algorithm, including differential attacks, multiple differential chain attacks, and algebraic attacks. Remarkably, there has been no published research on applying the cache timing attack to the Present algorithm, either domestically or internationally. In this paper, we employ a combination of the cache timing attack and a side-channel Trojan horse to obtain the output values of the S-box during the initial and second rounds of the encryption process. Subsequently, we integrate this data with a key recovery algorithm to ultimately retrieve the algorithm's master key. This research contributes to a better understanding of the vulnerabilities of the Present algorithm, with a focus on reducing similarity to existing texts. © 2023 IEEE.

关键词： algorithm's master key Cache timing attack Present algorithm S-box side-Channel attack

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Demystifying the Applications of Internet of Medical Things (IoMT) for smart health care system

Demystifying the Applications of Internet of Medical Things ...

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2023 International Conference on Data, Information and Computing science, CDICS 2023

作者： Begum, Ruqqaiya Swetha, Polisetty Tejasvi, Koti Jabbar, M.A. Vardhaman College of Engineering Dept. of Computer Science and Engineering Hyderabad India Hyderabad India

ISBN: (纸本)9798350382778

As Internet of Things (IoT) devices become more commonplace and are used in more aspects of daily life, a bright future for people, data, and processes is emerging. Because of its potential to enhance patient care as well as its capacity to deliver more trustworthy clinical data, boost productivity, and save costs, In recent years, the Internet of Medical Things (IoMT) has a strategic goal for future e-healthcare. It is understandable why so many healthcare organization's nowadays want to take advantage of what the IoMT has to offer. Its infrastructure includes interconnected medical equipment, software, and care systems and services. For everyone to understand how IoMT is enhancing the health care system with the aid of other technologies, we have described the implementation of IoMT in detail in this paper. Along with this, we have also discussed the different security concerns and difficulties the healthcare system is experiencing due to the IoMT's information-gathering shortcomings. © 2023 IEEE.

关键词： Electronic health record

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Yoga Pose Detection and Correction Using computer Vision 6

Yoga Pose Detection and Correction Using Computer Vision

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6th International Conference on Recent Trends in Advance Computing, ICRTAC 2023

作者： Hari Ram, S. Ramalingam, A. Ashok, A. Rajarajeswari, P. Dheenadhayalan, S. Gomathi, V. National Engineering College Dept. of Computer Science and Engineering Tamil Nadu Kovilpatti India

ISBN: (纸本)9798350394702

Yoga pose detection and correction aims to provide the user with conventional yoga poses, allowing the user to correct their poses with the help of real-time feedback. Yoga can cause prolonged issues like excessive pain and can also cause injuries such as slip disc, stiff neck, sprain and muscle pulls if practised incorrectly. This proposed tool can assist the user in practicing nine different yoga poses by utilizing computer vision, it analyzes the human poses, detects and corrects the user, ensuring a healthier lifestyle, and promotes well-being for people belonging to all age groups. This application provides a user-friendly environment that benefits users in the process of yoga learning and practice. Live webcams are used to detect the pose of the user and display the name of the Asana with accuracy. Corrections in angles would be mentioned and highlighted. This provides the user a choice to choose from i.e. Demo and Practice where a learning pathway consisting of several Asanas in the right order is accessible to the user and the detection of yoga poses is also available which enables the user to practice. The history of learned and practiced Asanas are maintained and displayed to the user. People nowadays prefer to stay at home since it is more comfortable. This situation demands a technology-driven yoga practice that is accessible to everyone, from any place across the globe. © 2023 IEEE.

关键词： computer vision

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Traffic Prediction Using Graph Neural Network

Traffic Prediction Using Graph Neural Network

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2023 IEEE Guwahati Subsection Conference, GCON 2023

作者： Sri, Lakshman S V Karthick, A. Akash, S. Anuradha, R. Sri Ramakrishna Engineering College Dept. of Aeronautical Engineering Coimbatore India Sri Ramakrishna Engineering College Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350337785

Traffic prediction is an important and challenging task in transportation management. Accurately predicting traffic patterns is crucial for reducing congestion, improving safety, and optimizing travel time. In recent years, graph neural networks (GNNs) have shown great potential in predicting traffic by taking into account the graph structure of road networks. In this project, we propose to develop a traffic prediction system using GNNs. The proposed system consists of three main components: data pre-processing, model development, and model evaluation. We first collect traffic data from various sources and pre-process it to remove noise and inconsistencies, and convert it into a suitable format for GNNs. We then develop a GNN model designed to capture the graph structure of the traffic network and use it to predict traffic patterns for a given time interval. The proposed model is trained and optimized using a loss function and evaluated using standard metrics such as root mean squared error (RMSE). The proposed traffic prediction system has the potential to significantly improve traffic management and reduce congestion by providing accurate traffic predictions. The GNN model can capture complex traffic patterns and dependencies between different parts of the road network, leading to more accurate predictions. Overall, this project aims to provide a better understanding of the potential of GNNs in traffic prediction and contribute to the development of more efficient and effective transportation management systems © 2023 IEEE.

关键词： Mean square error

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HealthLink: A Cutting-Edge System for Secure Healthcare Data with IoT, Blockchain, and IPFS 3

HealthLink: A Cutting-Edge System for Secure Healthcare Data...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Vijayakumar, Kallur V. Chethan, A.S. Muneshwara, M.S. Swetha, M.S. Anand, R. Shivakumara, T. Bmsit&m Dept. of Mathematics India Bmsit&m Dept. of Computer Science & Engineering India Bmsit&m Dept. of Information Science & Engineering India Bmsit&m Dept. of Mca India

ISBN: (纸本)9798350354348

In today's rapidly evolving healthcare landscape, the integration of cutting-edge technologies such as IoT and wearable devices has led to significant advancements, particularly in the realm of remote patient monitoring. Despite these advancements, the traditional client/server architecture prevalent in current implementations presents substantial challenges related to security and privacy, leaving healthcare systems vulnerable to various attacks. Consequently, stringent regulatory and security measures are imperative to safeguard health data. To address these challenges and meet regulatory requirements, transitioning to a distributed architecture is essential. Blockchain technology, renowned for its distributed nature and robust security features, offers a promising solution to mitigate the security risks inherent in IoT-based systems. Motivated by these considerations, this study introduces HealthLink - a secure healthcare framework that seamlessly integrates IoT and Blockchain *** is designed to facilitate remote patient monitoring, particularly for chronic diseases that require continuous oversight. The framework prioritizes security, scalability, and processing efficiency. Security measures include the use of re-encryption proxies combined with Blockchain for hash data storage, while access control is managed through smart contracts. To enhance Blockchain scalability, an off-chain IPFS-based database is employed for data storage, and the Ethereum Blockchain-based proof of authority is leveraged to expedite data storage processes. As a practical demonstration, we apply the HealthLink system to diabetes management, presenting execution results through system interfaces. Experimental findings highlight substantial enhancements in the security of healthcare systems compared to conventional methodologies, underscoring the potential of HealthLink to revolutionize remote patient monitoring and data security in healthcare. © 2024 IEEE.

关键词： Remote patient monitoring

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Accurate Detection of Aquatic Debris in Ocean Surfaces using AlexNet Algorithm over ResNet-50 Algorithm 3

Accurate Detection of Aquatic Debris in Ocean Surfaces using...

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3rd International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2023

作者： Kamal, T.M. Bharatha Devi, N. Saveetha School of Engineering Dept. of Computer Science Chennai India

ISBN: (纸本)9798350306989

This research study intends to detect the aquatic debris accurately on Ocean surfaces using Novel AlexNet algorithm in comparison with ResNet-50 algorithm. Novel AlexNet and ResNet-50 are the two groups considered for this research with 20 iterations done for each group whose G-power is 80% and confidence level is 95%. The dataset consists of 724 JPG file format images depicting clear ocean and 324 JPG file format images depicting aquatic debris, including images with noise. This work demonstrates that the Novel AlexNet algorithm achieves an accuracy of 93.77% which identifies objects accurately over the ResNet50 algorithm with an accuracy of 91.47% and there is no statistical significance difference between the Novel Alexnet Algorithm and ResNet-50 Algorithm for the value of p=0.076 (Independent Sample T-test p © 2023 IEEE.

关键词： Debris

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Relaxing Super Localization Frame Rate Requirements Utilizing a Novel 2D Interpolation Technique

Relaxing Super Localization Frame Rate Requirements Utilizin...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Tuccio, Giulia Afrakhteh, Sajjad Iacca, Giovanni Demi, Libertario University of Trento Dept. of Information Engineering and Computer Science Italy

ISBN: (纸本)9798350346459

Ultrasound Localization Microscopy (ULM) by-passes the conventional diffraction limit, allowing the imaging of the vasculature at a microscopic resolution through precise localization of intravenously injected microbubbles. Thanks to their resolution, ULM generated images hold the promise to be the next diagnostic frontier for diseases that modify the vascular structure, such as cancer. However, deploying ULM in clinical settings is currently limited by the prolonged acquisition times and high frame rates needed. To relax the high frame rate requirement, we propose a new time-efficient ULM (TEULM) pipeline. The proposed TEULM introduces the radial basis functions (RBFs) as interpolators upstream of the ULM framework, to recover the missing information consequence of a reduced frame rate. We test TEULM using in vivo Rat's Brain and Kidney datasets acquired at a high frame rate (1 KHz). The results confirm the ability of TEULM to reconstruct super-resolution (SR) images with a similarity score (Dice score) of 80% for both datasets when simulating a frame rate acquisition of 100 Hz;i.e., we can relax the frame rate requirement for ULM by a factor 10 while keeping the SR image quality acceptable. © 2023 IEEE.

关键词： Interpolation

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