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Smart Roads: U-Turn Accident Prevention System 4

Smart Roads: U-Turn Accident Prevention System

引用

4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023

作者： Johnson, Neena Ancy Jenifer, J. Khan, Aanya Jyothi, Akhila Karunya Institute of Technology and Sciences Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350300093

When discussing statistics of everyday road accidents in India, a very large contributing factor is accidents in hilly areas due to hairpin bends. These blind turns are highly dangerous and may more often than not result in fatal accidents. The low visibility results in the driver being extremely vulnerable to head-on collisions. Coming up with a preventive measure to this perilous situation is the prime focus of this paper. The proposed system in this paper is to, warn drivers of other vehicles at hairpin curves to avoid accidents involving human lives. This system is designed to allow residents and tourists to drive safely by warning them of blind corners and u-turns and reducing the possibility of accidents. This paper intends to reduce the chances of head-on collisions by implementing an accident prevention system. A prevention system, although new, should be comprehensible for a new user, to solve this issue, an existing system has been integrated with the proposed idea. © 2023 IEEE.

关键词： Light emitting diodes

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Drug Authentication and Counterfeit Drug Detection Using Blockchain 7

Drug Authentication and Counterfeit Drug Detection Using Blo...

引用

2023 7th International Conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Chandras, Atharva Agrawal, Satyam Chaudhary, Mithil Deshmukh, Anushka Shinde, Shilpa Ramrao Adik Institute of Technology Dept. of Computer Engineering Navi Mumbai India

ISBN: (纸本)9798350304268

Drug counterfeiting is a worldwide phenomenon which affects practically every industry involved with the healthcare sector in both developed and developing countries. This widespread smuggling and usage of counterfeit drugs has serious economic, health, and safety impacts on any country. In addition to this, the credibility of the healthcare system can be questioned and harmed if the counterfeit drugs find a way into the market and harm the public opinion about the pharmaceutical chain. An annual analysis done by the US Trade Representative office on rights protection in 2019 stated that up to 20% of the pharmaceutical supply sold in India were counterfeit and this has only increased since the pandemic. In an estimate done between 2020 to 2021, it was found that incidents of counterfeit and fake drugs had shot up to about 47 percent. Traditional methods of drug authentication have proven to be ineffective in detecting counterfeit drugs. Blockchain technology provides a promising solution to the problem of counterfeit drugs. The proposed system for detecting counterfeit drugs using blockchain technology consists of a blockchain network, a web application, and a database. The proposed system aims to provide an efficient and secure method of detecting counterfeit drugs using blockchain technology, which can enhance trust in the healthcare system and reduce the cost of drug authentication. © 2023 IEEE.

关键词： Blockchain Ganache Node js Solidity Truffle

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Deep Learning with Encoders for Intrusion Detection Systems (IDS) 10

Deep Learning with Encoders for Intrusion Detection Systems ...

引用

17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Budania, Vijay Ahmed, Mushtaq Verma, Anshita Malaviya National Institute of Technology Dept. of Computer Science and Engineering Jaipur India

ISBN: (纸本)9789380544472

An Intrusion Detection System (IDS) is often used to keep safe and efficiently utilise communication network. And generally this is achieved by monitoring the network regularly for possible intrusions. Nowadays in networks, zero-day attacks are common type of intrusions. So it became necessary to use IDS, which is capable of detecting zero-day attacks. Machine Learning (ML) algorithms are suitable in designing such IDS. Deep Learning (DL), being part of ML, have promising approaches that can be used in designing IDS, which is capable of detecting intrusions of new and old types. This paper proposes DL based IDS which create model of normal network traffic. This model classifies attacks based on the various features present in the dataset. The proposed model uses a Convolution Neural Network, bi-directional Long Short Term Memory (LSTM), and a stack of encoders to handle spatial and temporal features more effectively. The model achieves a low False Positive Rate and high Detection Rate compared to existing models. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Zero-day attack

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An Incremental Algorithm for (2-ϵ)-Approximate Steiner Tree Requiring O(n) Update Time 11

An Incremental Algorithm for (2-ϵ)-Approximate Steiner Tree...

引用

11th International Symposium on Computing and Networking, CANDAR 2023

作者： Raikwar, Hemraj Karmakar, Sushanta Indian Institute of Technology Guwahati Dept. of Computer Science and Engineering Guwahati India

ISBN: (纸本)9798350306705

Given an undirected connected weighted graph with non-negative edge weights and a subset of vertices called terminals, the goal of the Steiner tree problem is to find a tree that spans the terminals such that the weight of the tree is minimized. A dynamic graph is a graph where the edge set or the vertex set or both may change with time. In this paper, first, we give a lower bound on the worst case update time for maintaining a(2-\epsilon)-Approximate Steiner tree (\epsilon being a small fraction) based on MST heuristic in a general dynamic graph with edge insertions and deletions. Then we propose an incremental algorithm for the Steiner tree problem in general dynamic graphs with edge insertions. We consider a weighted undirected connected graph with positive real edge weights and each update inserts an edge with a specific weight in the graph. The goal is to maintain a Steiner tree of the terminals. The algorithm maintains a(2-\epsilon)-Approximate Steiner tree in O(n) update time where n is the number of vertices in the graph. © 2023 IEEE.

关键词： Undirected graphs

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5G the Missing Piece in Digital Transformation of the Construction Sector 28

5G the Missing Piece in Digital Transformation of the Constr...

引用

28th International computer Science and engineering Conference, ICSEC 2024

作者： Chnaidini, Shaik Khan, M. Jebran Ullah, Fasee Khan, Arafat Ahmad Prashar, Deepak Gulf American University Dept. of Civil Engineering Fujairah United Arab Emirates Sarhad University of Science and Information Technology Dept of Computing and Information Technology Peshawar Pakistan Uinversiti Teknology Petronas Dept. of Computer and Information Sciences Seri Iskandar Malaysia Khonkaen University Dept. of Computer Science Khon Kaen Thailand Lovely Professional University Dept. of Computer Science and Engineering Punjab India

ISBN: (纸本)9798350366860

The 5th generation of wireless technology with a continuum leap rushing towards the future in the world of communication has a puzzle that enables the autonomous machine to work in site making a louder voice that shows the era where even if we cannot be fully robotic, we can make the machines do the work by sitting on a faraway control room. Making ways clear to see the work done miles away on construction sites the 5th generation has not only brought the people close through communication but also made them work collegiately with a clearer view front. The paper discusses 5G and the other related technologies that are emerging all over the world and how it is needed specifically in the construction industry. In the present paper, we tried to shed light on the acceptance and implementation of 5G technology in the construction sector. It is seen that the construction sector in India is lagging behind when it comes to implementation and availability of required support and resources for the 5G implementation. © 2024 IEEE.

关键词： Construction industry

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Hate Speech Detection in Indian Languages: A Brief Survey 2

Hate Speech Detection in Indian Languages: A Brief Survey

引用

2nd IEEE International Conference on Data, Decision and Systems, ICDDS 2023

作者： Rameez Mohammed, A. Madhukumar, S.D. National Institute of Technology Dept. of Computer Science and Engineering Kerala Calicut India

ISBN: (纸本)9798350314168

Social media has revolutionized communication and content publishing. Anonymity and mobility afforded by social media is also an effective medium for dissemination of hate messages, which can lead to undesired outcomes in the society. Prevalence of hate speech is a global problem. This paper is intended to highlight the mechanisms to address the same in the Indian context. This work aims to provide a concise overview of the various machine learning, deep learning, and transformer methods to detect hate speech in social media text written in Indian languages, as detailed in recent research literature. Besides, a discussion some of the available monolingual and code-mixed datasets to train such classifiers and the commonly adopted strategies to address the data scarcity in Indian languages is also included. © 2023 IEEE.

关键词： Deep learning

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Pseudonymous Decentralised Reputation System 9

Pseudonymous Decentralised Reputation System

引用

9th International Conference on Smart Computing and Communications, ICSCC 2023

作者： Nalini, N. Kumar, Anshul Sharma, Megha Sil, Aniruddha Khan, Womika Nitte Meenakshi Institute of Technology Dept. of Computer Science & Engineering Bangalore India

ISBN: (纸本)9798350314090

In this paper, we propose a novel pseudonymous decentralized reputation system that aims to establish trust within decentralized networks. The system allows users to maintain pseudonymous identities while ensuring their reputation scores are transparent, trustworthy, and resistant to manipulation. We review existing reputation systems and discuss their limitations. Our proposed system incorporates cryptographic techniques, a consensus algorithm, and distributed data storage to ensure data integrity, privacy, and scalability, specifically designed for the Decentralized Finance (DeFi) ecosystem. We present an implementation of our system, focusing on its application in DeFi platforms, and evaluate its performance against various attack vectors. Finally, we discuss the implications of our system on decentralized financial applications, such as lending and borrowing protocols, and future research directions. Lastly, we explore the broader implications of our decentralized reputation system for the DeFi ecosystem, identifying potential applications in areas such as decentralized exchanges, insurance, and asset management. © 2023 IEEE.

关键词： Blockchain

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An Efficient Deep Learning Technique for Intrusion Detection in Wireless Sensor Network 3

An Efficient Deep Learning Technique for Intrusion Detection...

引用

3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Kumari, Prity Tiwari, Rakesh Kumar Technocrats Institute of Technology and Science Dept. of Computer Science Engineering Bhopal India

ISBN: (纸本)9798350322842

Predicting intrusion detection in a wireless sensor network (WSN) involves using machine learning algorithms to analyze network traffic data and predict whether an intrusion or security breach will occur. The goal of intrusion prediction is to provide advanced warning of potential attacks and allow for proactive measures to be taken to prevent or mitigate the attack's impact. Several machines and deep learning algorithms can be used for intrusion prediction in WSNs. This research describes a practical deep-learning approach for Intrusion Detection in WSN based on artificial neural networks. Spyder IDE of python with version 3.7 is used for the simulation work. The results of the simulations demonstrate that the anticipated model is accurate 99.99% of the time. © 2023 IEEE.

关键词： Python

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A Cluster-based Virtual Edge Computation Offloading Scheme for MEC-enabled Vehicular Networks 26

A Cluster-based Virtual Edge Computation Offloading Scheme f...

引用

26th Pan-Hellenic Conference on informatics, PCI 2022

作者： Sotiriadis, Leontios Mamalis, Basilis Pantziou, Grammati University of West Attica Dept. of Informatics and Computer Engineering Greece

ISBN: (纸本)9781450398541

Internet of Vehicles (IoV) has received a great deal of attention in recent years from many researchers. Recently, vehicular edge computing has been a new paradigm to support computation-intensive and latency-sensitive services in IoV. Moreover, with the cellular-vehicle to everything technology, many tasks and applications can be efficiently offloaded to another node for processing. In this paper a novel cluster-based virtual edge computation offloading scheme is proposed, which has as its main objective to efficiently find the most suitable multi-hop neighbor to act as a virtual edge computing (VEC) server for task offloading. The proposed scheme is initially based on the formation and maintenance of multi-hop clusters with high stability, whereas its efficiency is further enhanced by the local/distributed computations taking place where it's possible. © 2022 ACM.

关键词： Computation offloading

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Cloud engineering-based on Machine Learning Model for SQL Injection Attack

Cloud Engineering-based on Machine Learning Model for SQL In...

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2023 International Conference on Communication, Circuits, and Systems, IC3S 2023

作者： Singh, Kavita Kokardekar, Sakshi Khonde, Gunjan Dekate, Prajakta Badkas, Nishita Lachure, Sagar Yeshwantrao Chavan College of Engineering Dept. of Computer Technology Mh Nagpur India

ISBN: (纸本)9798350325904

The entire IT sector has been altered by Cloud engineering, which is also continually coming up with new, creative solutions to everyday issues. A systematic method for the commoditization, standardization, and governance of cloud computing applications is provided by cloud engineering, which is the application of the engineering discipline to cloud computing. These days, a lot of businesses and individual users keep enormous amounts of data on the cloud. The information in the data could be sensitive or could be pertinent to the client or the user. Through a variety of harmful methods, the attackers attempt to obtain private data. One such attack is a SQL Injection Attack, in which a hostile user attempts to get unauthorized access to sensitive cloud data by injecting malicious SQL queries. In this paper, a machine learning model is proposed to identify this kind of attack. The Count-Vectorizer approach and the TF-IDF Vectorizer approach are used to test 3 different machine learning models on two different datasets, one with 4200 data items and the other with 30100 data items, both of which contain SQL queries. The models were built using the Random Forest, XgBoost, and Extra Trees Classifier algorithms, respectively. After deploying the models to the test, it was found that with the test size 0.2, Extra trees classifier shows the highest accuracy on dataset of 4200 entries on both the approaches TF-IDF Vectorizer (TV) and Count Vectorizer (CV) and for the dataset of 30100 entries the XgBoost Classifier gives high accuracy with Count Vectorizer approach while XgBoost gives highest accuracy with TF-IDF Vectorizer approach. © 2023 IEEE.

关键词： Cloud computing

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