{"title":"Adversarial Attacks against Neural Networks using Projected Gradient Descent with Line Search Algorithm","authors":"Lourdu Mahimai Doss P, M. Gunasekaran","doi":"10.1109/ViTECoN58111.2023.10157254","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157254","url":null,"abstract":"The aim of the research is to investigate the security challenges posed by the deployment of neural networks, with a focus on evasion attacks. The research uses the MNIST dataset as a representative example and employs the projected gradient descent with the line search (PGDLS) algorithm to craft adversarial examples that can deceive the network into making incorrect predictions. In this research, we demonstrate that neural networks are vulnerable to such attacks and investigate PGDLS ability to craft adversarial examples. The research also aims to provide insights into the security challenges posed by evasion attacks and to contribute to the ongoing research into the security of neural networks. The ultimate goal of the research is to raise awareness of the security risks associated with the deployment of neural networks and to provide valuable information for the development of robust and secure models. In order to prevent neural networks from malfunctioning or being misused in real-world scenarios, ongoing research is essential to enhance their security.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124019326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jagath A.P, Ganesh Moorthy G, Muthu Murugan M, Aarthi. V.P.M.B., Sibi Rajan R, M. Sohaib
{"title":"Design a PnR Flow Implementation for Different IR Drop Targets","authors":"Jagath A.P, Ganesh Moorthy G, Muthu Murugan M, Aarthi. V.P.M.B., Sibi Rajan R, M. Sohaib","doi":"10.1109/ViTECoN58111.2023.10157617","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157617","url":null,"abstract":"This paper describes the development of a Place-and-Route (PnR) flow implementation for different IR drop targets. IR drop is a significant concern in chip design, as it can lead to undesirable effects such as timing violations and power loss. Therefore, optimizing the IR drop is crucial for efficient chip design. In this project, we develop a PnR flow that can handle different IR drop targets, which will be achieved by modifying the placement and routing stages. The flow will be compared to existing PnR flows and evaluated using various benchmarks. The outcomes will show how well the suggested approach works and how it can handle various IR drop targets. Overall, this project will contribute to improving the efficiency and reliability of chip design by providing a flexible PnR flow that can handle different IR drop targets.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126146545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Dhivya, Manoj Kumar S, Mathesh J, V. Thanikaiselvan, Hemalatha Mahalingam, Rengarajan Amirtharajan
{"title":"Secure health data transmission on IOT","authors":"R. Dhivya, Manoj Kumar S, Mathesh J, V. Thanikaiselvan, Hemalatha Mahalingam, Rengarajan Amirtharajan","doi":"10.1109/ViTECoN58111.2023.10156896","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10156896","url":null,"abstract":"Data security is essential to the e-healthcare industry for protecting patients' confidential information. It is necessary to continuously monitor the patient's health to give them the proper medical care. The proposed work develops a Raspberry Pi cryptosystem by sending real-time patient health data to the physician via the Thing Speak cloud environment. In order to create the highly random keys for encrypting the color medical images and sensor data (temperature, heartbeat, medical images), this research uses numerous chaotic maps in a single procedure. Firstly, the shuffling algorithm based on a logistic map is designed to shuffle the image pixels randomly. Then, the diffusion algorithm based on circle map is developed to diffuse the shuffled image pixels. The effectiveness of the proposed algorithm is analysed based on MSE (Mean Squared Error), PSNR (Peak Signal-to-Noise), Entropy, Histogram, and correlation is calculated analyses.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129531263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Real-Time Sign Language Detection","authors":"Sangeeta Kurundkar, Arya Joshi, Aryan Thaploo, Sarthak Auti, Anish Awalgaonkar","doi":"10.1109/ViTECoN58111.2023.10157784","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157784","url":null,"abstract":"Lack of communication or miscommunication brought on by linguistic problems can lead to awkward situations in today's culture. Those who are deaf or have trouble hearing use sign language, a visual form of communication, to communicate. It communicates meaning through hand gestures and body language. Yet not everyone is able to interpret sign language, which might result in miscommunication. A system was developed employing cutting-edge technologies to address this problem, including deep learning, machine learning, convolutional neural networks, computer vision, TensorFlow, and Python. This technology is made to accurately detect and identify sign language motions in real-time. The system develops a real-time sign language recognition tool using OpenCV. The 26 letters in American Sign were categorised using a CNN classifier. The use of technology to bridge communication gaps and create inclusive environments is crucial in our society. This system's high accuracy rate is an excellent indication of its reliability, providing a promising solution for individuals who use sign language to communicate. It would be interesting to learn more about the specific CNN classifier used in the project and how it was trained to recognize ASL gestures. Overall, the implementation of this technology can create more inclusive and accessible environments, ensuring that everyone can communicate effectively, regardless of their abilities or differences.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128411259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automated Brain Tumor detection using multi-label images of MRI scans and CNNs","authors":"Aman Patel, Nidumoli Gowthami Priya, G. Divya","doi":"10.1109/ViTECoN58111.2023.10157529","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157529","url":null,"abstract":"Numerous medical diagnostic applications now heavily rely on automatic defect detection in medical imaging. Automatically detecting tumors by MRI is essential for treatment planning because it offers details on aberrant tissues. Due to the volume of data required, this strategy is impracticable. As a result, to lower the rate of human death, trustworthy and automatic classification techniques are required. Automated tumor detection techniques are therefore being created to free up radiologist time and attain proven accuracy. Brain tumor, which develops as a result of the abnormal development and division of brain cells, eventually turn into brain cancer. The study of human health benefits greatly from the use of computer vision since it is used to eliminate the requirement for precise human judgement. The most reliable diagnostic tools include MRI scans, CT scans, and X-rays. Secure imaging techniques within magnetic-resonance imaging (MRI). In this study, the noises present in an MR image were removed using a morphological opening to the pre-processing. Binary thresholding and Neural Network segmentation methods were then used to accurately detect tumors. Our model will assess if the person has a brain tumor or not. To increase the accuracy of different models and scaling methods such as Efficient B2, B3, and B6, we want to test and experiment with them.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128453195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Novel Two Dimensional Chaotic Map for Secure Image Communication","authors":"Sakshi Patel, T. V","doi":"10.1109/ViTECoN58111.2023.10157411","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157411","url":null,"abstract":"In present era of fast multimedia communication, there are many loop holes where the security is compromised. We have developed a new two-dimensional chaotic map for secure multimedia communication in this research. The generated two dimensional triangle function combined discrete chaotic map (2D-TFCDM) is rigorously studied and tested. The various randomness test applied on the novel map are: National Institute of Standards and Technology (NIST) test suite, attractor plot, sensitivity test, bifurcation diagram and Lyapunov exponent. Generated map is utilized in image encryption, where it is combined with hash functions for better security. The generated map passes all the tests and demonstrates that the novel discrete system is extremely chaotic and can be used for cryptography applications. Simulation results obtained from the proposed methodology is compared with the existing techniques that show the extreme chaotic nature of the proposed system.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129093530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Color Compensation Based Fusion for Enhancement of Weakly Artitifical Illuminated Indoor Images","authors":"M. Kanagavel, T. V","doi":"10.1109/ViTECoN58111.2023.10157246","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157246","url":null,"abstract":"In this article, a new approach is introduced to enhance the weakly artificial illuminated indoor images by blending three color compensated versions obtained by Color Equalization (CE), Color Mixing (CM) and Gray-World (GW) methods. This method ignores the disadvantages of blue dominancy, green dominancy and black artefacts results respectively due to CE, GW and CM and this forms prior for this fusion approach. To fuse the advantages of all three enhanced versions of low illuminated images, the multi-scale image fusion technique is employed. To get the information of background scenes, contrast limited adaptive histogram equalization (CLAHE) is applied to the blended image. The experimental results illustrate that the approach proposed in this work outperforms the existing methods.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125664059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling, Simulation and Implementation of Photovoltaic Panel Based on High Accuracy Two-Diode Model","authors":"D. Dash, Aviral Soni, Harsha Sharan, Prajwal Sinha, Rahul Saxena, Harsh Singh","doi":"10.1109/ViTECoN58111.2023.10157000","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157000","url":null,"abstract":"A high precision two-diode photovoltaic panel is what the current work's conclusion suggests. Mathematical calculations explains the functioning of two-diode PV circuit, this model is analyzed. The photocurrent 2 diodes, a resistor which is parallel, and a resistor in series and source are all components of this circuit. Since the Proteus software has a large library of electronic models and microcontrollers, it is used to model and simulate the associated model rather than MATLAB/Simulink. Also, the more precise and nearby software is used to test the suggested model before the full hardware implementation is produced in response to successful simulation results for the same component circuit.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125554368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Anomaly Detection in Data Centers using Isolation Networks","authors":"Samirit Saha, Beena B. M.","doi":"10.1109/ViTECoN58111.2023.10157102","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157102","url":null,"abstract":"The given research paper proposes a direction or an approach that is novel and efficient for the purpose of detecting anomalies in data centers using isolation networks. Data centers are critical infrastructure in modern society, responsible for hosting and managing large amounts of data and providing computational resources for a variety of applications. As such, it is crucial for making sure that the security is maintained and optimal performance of data centers. The process of detecting anomalies is a key component of this effort, as it can help identify security threats and performance issues. The proposed approach uses isolation networks, a type of unsupervised machine learning algorithm, to identify anomalies in server and network behavior based on input features such as CPU utilization, memory usage, and network traffic. The paper evaluates the performance of the approach using a publicly available dataset of data center metrics, and show that it can achieve high accuracy in identifying anomalies while maintaining a low false positive rate. The paper's results suggest that isolation networks have significant potential for improving the security and performance of data centers, and we discuss several potential avenues for future research in this area. Overall, this paper contributes to the growing body of literature on machine learning for data center management and highlights the importance of anomaly detection in ensuring the reliability and security of these critical infrastructure systems.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126540173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vishal Kasyap S, R. K., S. Uma, A. R, V. Thanikaiselvan, Hemalatha Mahalingam
{"title":"Simulation of a Wheeled Robot using ROS","authors":"Vishal Kasyap S, R. K., S. Uma, A. R, V. Thanikaiselvan, Hemalatha Mahalingam","doi":"10.1109/ViTECoN58111.2023.10157323","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157323","url":null,"abstract":"Simulators are the tools used to study the behaviour of an entity, in this case, Wheeled Mobile Robots. These simulators played a significant role in robotics research as a tool for effectively testing algorithms, concepts and strategies. One such widely used simulator in the field of robotics is Gazebo. This paper overviews how a differential drive robot is simulated using Gazebo in a ROS environment. ROS is an open-source robot operating system. As ROS is open-source, many people have contributed to building robot software systems. These software systems can be used for various research and other requirements accordingly. Gazebo enables Simulation of the world, physical model, sensors and control system through the Unified Robot Description Format (URDF) file. ROS is interfaced with Gazebo to allow the implementation and usage of various robotic software systems and tools on the simulated Robot. In this paper, Localisation, Mapping and Path Planning algorithms are being implemented on the mobile Robot.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123011398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}