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Secured intelligent transportation with privacy retention through blockchain framework

Journal of Intelligent and Fuzzy systems 2024年第4期46卷 10507-10521页

作者： Kaur, Gaganpreet Shobana, M. Kavin, F. Sellakumar, S. Meenakshi, D. Bharathiraja, N. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Networking and Communications Faculty of Engineering and Technology SRM Institute of Science and Technology KTR Chengalput Tamil Nadu Chennai India Department of Electronics and Instrumentation M.S. Ramaiah Institute of Technology Karnataka India Department of Mechanical Engineering Saveetha Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering Tagore Engineering College Tamil Nadu India

The Secured Independent Intelligent Transport system (SIITS) is poised to revolutionize traditional transport management systems, leveraging autonomous vehicles (AVs) connected through an open-channel Internet to link Traffic Command Centers (TCCs), Road Side Units (RSUs), and AVs within the SIITS framework. However, this reliance on the Internet exposes users to various security risks, safety vulnerabilities, and other challenges that impede the progress of SIITS applications. In this method, ensuring robust security management and trustworthiness is paramount for the long-term adoption of this innovative trend. While previous efforts have focused on integrating security methods from multiple disciplines into a unified reference design, this article presents a reference architecture primarily centered around ITS safety. Additionally, the article introduces a proposed framework for enhancing ITS safety, addressing the confidence issues. To further address these challenges, the article offers categorization of goods, Big Data methods and services, and validates the utility of ITS business analytics for corporate applications through a groundbreaking multi-tier ITS security architecture. © 2024 - IOS Press. All rights reserved.

关键词： Big data

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Smart Agri Guide

Smart Agri Guide

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2023 Intelligent Computing and Control for engineering and Business systems, ICCEBS 2023

作者： Kavitha, D. Desigan, M. Subanandham, E.R. Madhan, H. Latha, K. Hemavathi, S. Sri Sairam Engineering College Department of Computer Science and Engineering Chennai India Sri Sairam Engineering College Department of Mechanical Engineering Chennai India

ISBN: (纸本)9798350394580

Access to accurate and current information is essential given how quickly the agriculture industry is changing. For farmers, researchers, students, and hobbyists, the suggested solution offers a wealth of information about diverse crops, cultivation methods, and the worldwide agricultural scene. Our website offers a user-friendly platform with detailed articles, pictures, and information about a variety of crops, from common ones like wheat, rice, and maize to uncommon variants and specialty crops. View in-depth profiles that cover the history, geography, growing requirements, and harvesting techniques of various crops. The website goes beyond the fundamentals, exploring modern advancements in agricultural technology, pest and disease management, and sustainable farming methods. The program serves as the entrance to a growing online market for agricultural crops that connects farmers, suppliers, and customers. The application gives a ground-breaking platform that alters how agricultural products are purchased and sold. Farmers and producers may easily advertise their produce, get in touch with new customers, and broaden their market. By offering capabilities for inventory management, price tactics, and logistical assistance, the program streamlines the selling process. © 2023 IEEE.

关键词： agriculture disease management sustainable farming website

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A Comprehensive Survey of Cybercrime and Cybersecurity 5

A Comprehensive Survey of Cybercrime and Cybersecurity

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5th IEEE International Conference on Advances in Electronics, computers and Communications, ICAECC 2023

作者： Shindagi, Kunaal Shirish Koppad, Khushi Vikram Jayakkanavar, Abhilasha Gorabal, S.V. Jain College of Engineering and Research Department of Computer Science and Engineering Belagavi India Jain College of Engineering and Research Department of Mechanical and Engineering Belagavi India

ISBN: (纸本)9798350305449

In the futuristic context, 'cybercrime' has become more hazardous to the nation's youth because felons and cybercrime victims are reported worldwide with false geographic information. any person in any area with a region is susceptible to a cyber threat, according to the futuristic scenario because protecting data has become one of the largest concerns in the modern world, cybersecurity is essential in the field of information technology. Cyber security is crucial to protect businesses and individuals from spammers and cyber culprits because one security branch Can make the private information of millions of people available. These branches can lead to a loss of client trust and have a single financial impact on the business. Cybercrime is expanding daily and it is the first thing that comes to mind when we think of cybersecurity. It is crucial to be aware of the threat that information technology (IT) poses and how to defend against it. Knowing what cyber security is and being able to use it effectively are essential in the modern world, which is run almost entirely by information technology. Cyber security seeks to shield users from harm, secure their safety, and safeguard personal information while they browse the internet. This research aims the acknowledge the extent of awareness among youth about cybercrime and cybersecurity. © 2023 IEEE.

关键词： Cybersecurity

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IoT-Enhanced Smart Carry to Prevent Spinal Cord Injury by Weight Monitoring

IoT-Enhanced Smart Carry to Prevent Spinal Cord Injury by We...

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2023 International Conference on Recent Advances in science and engineering Technology, ICRASET 2023

作者： Varshitha, D.N. Shreya, B.S. Nidhi Shree, S.P. Vinutha, D.C. Gourav, R. Chetan, P. Mysuru India Vidyavardhaka College of Engineering Computer Science Engineering Department Mysuru India Vidyavardhaka College of Engineering Mechanical Engineering Department Mysuru India

ISBN: (纸本)9798350306927

The necessity for students to carry heavy backpacks, laden with books and study materials, is prevalent in numerous educational institutions worldwide, particularly in remote areas where walking long distances is common. However, this practice poses significant health risks, leading to issues like improper posture, neck, shoulder, and back strain, and potentially severe spinal damage. To address these concerns, our study proposes an IoT-based solution. Utilizing components such as Arduino 101 processing board, a Bluetooth module, accelerometers, force-sensitive resistors, backpacks, and a mobile application, our solution aims to alert students when their backpack weight exceeds a predetermined threshold. This paper discusses the methodology, results, and relevant literature associated with our proposed solution. © 2023 IEEE.

关键词： Accelerometers

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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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Improving Information Delivery Effectiveness and Efficiency Using WebVR Technology 23

Improving Information Delivery Effectiveness and Efficiency ...

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8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Pratama, Ardiyan Nur Akbar, Muhammad Aminul Pinandito, Aryo Informatics Engineering Department Universitas Brawijaya Faculty of Computer Science Indonesia Information System Department Universitas Brawijaya Faculty of Computer Science Indonesia

ISBN: (纸本)9798400708503

In this digital era, attracting new students from outside the region to enter a college or university is difficult. This problem can be solved with good marketing and information dissemination techniques. Information is a type of data that has been processed and organized so that it has relevant meaning for the recipient. Useful information can be used to help make decisions, gain new knowledge, or solve problems. One medium for providing information is by using videos that can be uploaded to YouTube for dissemination. However, problems arise when the information depends on the point of view of the video content creator, who may not provide enough information sought by users in their videos. Virtual reality (VR) technology can be pursued as one of the solutions to overcome the lack of detail and control in videos for users to get the expected information. One of the technologies in VR that allows people to explore a three-dimensional virtual world on a web platform is the 360° WebVR technology. Since users have full control over what can be seen using WebVR, it is expected that this technology can assist users in getting deeper and detailed information related to their needs. This study aims to determine the effectiveness and efficiency of using YouTube videos and WebVR in distributing information and delivering detailed information to users. The results show that WebVR technology has the potential to provide greater control over more detailed information to users who use it, in contrast to traditional two-dimensional video playback technology. © 2023 ACM.

关键词： Virtual reality

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Sailfish Optimization with Deep Learning Based Oral Cancer Classification Model

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computer systems science & engineering 2023年第4期45卷 753-767页

作者： Mesfer Al Duhayyim Areej A.Malibari Sami Dhahbi Mohamed K.Nour Isra Al-Turaiki Marwa Obayya Abdullah Mohamed Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Computer Science College of Computing and Information SystemUmm Al-Qura UniversityMecca24382Saudi Arabia Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh4545Saudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt

Recently,computer aided diagnosis(CAD)model becomes an effective tool for decision making in healthcare *** advances in computer vision and artificial intelligence(AI)techniques have resulted in the effective design of CAD models,which enables to detection of the existence of diseases using various imaging *** cancer(OC)has commonly occurred in head and neck *** identification of OC enables to improve survival rate and reduce mortality ***,the design of CAD model for OC detection and classification becomes ***,this study introduces a novel computer Aided Diagnosis for OC using Sailfish Optimization with Fusion based Classification(CADOC-SFOFC)*** proposed CADOC-SFOFC model determines the existence of OC on the medical *** accomplish this,a fusion based feature extraction process is carried out by the use of VGGNet-16 and Residual Network(ResNet)***,feature vectors are fused and passed into the extreme learning machine(ELM)model for classification ***,SFO algorithm is utilized for effective parameter selection of the ELM model,consequently resulting in enhanced *** experimental analysis of the CADOC-SFOFC model was tested on Kaggle dataset and the results reported the betterment of the CADOC-SFOFC model over the compared methods with maximum accuracy of 98.11%.Therefore,the CADOC-SFOFC model has maximum potential as an inexpensive and non-invasive tool which supports screening process and enhances the detection efficiency.

关键词： Oral cancer computer aided diagnosis deep learning fusion model seagull optimization classification

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UNet Based onMulti-Object Segmentation and Convolution Neural Network for Object Recognition

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computers, Materials & Continua 2024年第7期80卷 1563-1580页

作者： Nouf Abdullah Almujally Bisma Riaz Chughtai Naif Al Mudawi Abdulwahab Alazeb Asaad Algarni Hamdan A.Alzahrani Jeongmin Park Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Information Technology Department College of Computing and InformaticsSaudi Electronic UniversityRiyadh13316Saudi Arabia Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Republic of Korea

The recent advancements in vision technology have had a significant impact on our ability to identify multiple objects and understand complex *** technologies,such as augmented reality-driven scene integration,robotic navigation,autonomous driving,and guided tour systems,heavily rely on this type of scene *** paper presents a novel segmentation approach based on the UNet network model,aimed at recognizing multiple objects within an *** methodology begins with the acquisition and preprocessing of the image,followed by segmentation using the fine-tuned UNet ***,we use an annotation tool to accurately label the segmented *** labeling,significant features are extracted from these segmented objects,encompassing KAZE(Accelerated Segmentation and Extraction)features,energy-based edge detection,frequency-based,and blob *** the classification stage,a convolution neural network(CNN)is *** comprehensive methodology demonstrates a robust framework for achieving accurate and efficient recognition of multiple objects in *** experimental results,which include complex object datasets like MSRC-v2 and PASCAL-VOC12,have been *** analyzing the experimental results,it was found that the PASCAL-VOC12 dataset achieved an accuracy rate of 95%,while the MSRC-v2 dataset achieved an accuracy of 89%.The evaluation performed on these diverse datasets highlights a notably impressive level of performance.

关键词： UNet segmentation blob fourier transform convolution neural network

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PACE: Reputation-Driven Hierarchical Incentive Mechanism for Trusted Healthcare Transactions in Model Marketplace

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IEEE Transactions on Consumer Electronics 2024年第1期71卷 1571-1583页

作者： Lu, Jianfeng Dou, Xiaochi Rathore, Bharati Jhaveri, Rutvij H. Seid, Abegaz Mohammed Erbad, Aiman Wuhan University of Science and Technology School of Computer Science and Technology Wuhan430065 China Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China Ministry of Education Key Laboratory of Social Computing and Cognitive Intelligence Dalian University of Technology China United Kingdom Pandit Deendayal Energy University Department of Computer Science and Engineering School of Technology India Hamad Bin Khalifa University College of Science and Engineering Doha Qatar Qatar University College of Engineering Doha Qatar

Federated learning-based model marketplaces have the potential to securely leverage healthcare data for efficient healthcare transactions. However, the willingness to participate in this marketplace is severely hindered by self-interested model sellers, who maximize their personal gains via distorting the quality of their models. To this end, we propose a rePutation-driven hierArchical inCentive mEchanism, called PACE, which combines contract cooperation and game pricing to motivate model sellers to be honest, thereby improving the sustainability of the model marketplace via two-layer cooperation. Specifically, at the training layer, we design a reward payment rule based on multidimensional contracts, while at the trading layer, we use a competitive market pricing game to develop the accuracy pricing rule. In particular, the above rules cleverly combine the fine-grained model sellers' reputations with the willingness of healthcare devices to indirectly affect the model sellers' utilities. Theoretically, we prove that PACE can effectively incentivize model sellers to truthfully report model quality while satisfying both individual rationality and incentive compatibility with a fairness guarantee. Experimental results conducted on four real-world datasets show that our PACE improves the global performance by up to 12.85% and reduces the global loss by at least 19.23% compared with the state-of-the-art baselines. © 1975-2011 IEEE.

关键词： Marketplaces

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A Machine Learning Based Prediction of Machining Characteristics of Super Alloy in EDM Using Green Synthesized Nano Copper Oxide Dispersed Bio Dielectric Fluid 1st

A Machine Learning Based Prediction of Machining Characteris...

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1st International Conference on Advanced Materials Manufacturing and Structures, ICAMMS 2024

作者： Baskar, S. Pragadish, N. Shanmugapriya, P. Perumal, S. Vishvanath Department of Mechanical Engineering Rajalakshmi Engineering College Thandalam Tamilnadu Chennai602105 India Department of Mechanical Engineering Rajalakshmi Institute of Technology Tamilnadu Chennai600124 India Computer Science and Business Systems Rajalakshmi Engineering College Thandalam Chennai602105 India Department of Mechanical Engineering S.A. Engineering College Tamilnadu Chennai600077 India

ISBN: (纸本)9783031725265

This present study describes the various machine learning techniques such as artificial neural network (ANN), and support vector machine (SVM) are used to predict and genetic algorithm (GA) is used to optimize the material removal rate (MRR) and surface roughness (SR) of Ti6Al4V in electrical discharge machining (EDM) by using nano copper oxide dispersed bio dielectric fluid. MRR and SR were estimated during EDM under the various operating parameters such as discharge voltage, current and discharge time. In this study, an optimal ANN architecture has been determined as 3-10-10-2 and SVM factors were altered by using grid search method. The predicted R-value of SVM is 0.9999 and the minimum mean absolute percentage error for MRR is 0.0085% and SR is 0.0564%. In addition to that, GA optimization has been employed by using objective function developed from Box-Behnken design and enhanced 6.41% and 16.94% in MRR and SR respectively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Support vector machines

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