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Implementing Robust Security Protocols for Virtual Images in Cloud Computing Platform

Implementing Robust Security Protocols for Virtual Images in...

2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024

作者： Tiwari, Shiv Kumar Gupta, Manish Neogi, Subhrendu G. Amity School of Engineering and Technology Amity University Department of Computer Science Engineering Gwalior India The Neotia University Department of Computer Science Engineering West Bengal India

ISBN: (纸本)9798331517953

The new technology, with the aid of newly emerging knowledge known as cloud computing, can provide resources remotely and on demand. With the use of cloud computing, users can operate in settings where they are not dependent on physical infrastructure. Numerous protocols facilitate the utilization of cloud computing resources. Cloud computing is Internet-based technology that is made available to consumers of its resources and services and is billed depending on demand and usage. All cloud servers cannot see the precise place where the user is to be configured. User-generated secure keys are employed in the proposed work for both virtual machine (VM) switching and authentication. Every time a valid user is authenticated, a secure pass key is utilized to guarantee security and authentication between the user and the system. © 2024 IEEE.

关键词： Cloud platforms

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Automated Customer Feedback Generation Using Facial Expression Through OpenCV 1

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6th International Conference on Smart Computing and Informatics, SCI 2024

作者： Ayushi Arora, Deepak Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Uttar Pradesh Lucknow Campus Lucknow India

ISBN: (数字)9789819619818

ISBN: (纸本)9789819619801

A business needs to work on the right problems to be able to grow. These problems can only be provided by the people who are using the product or service made by the business. Accurate customer feedback is what allows a business to set its priorities straight. Thus, in this paper, we have attempted to make a simple and easy-to-use tool from already existing resources that will provide real-time customer reviews to business owners which will help them in improving their service. The result of the model execution includes the performance of various concepts that are face detection, face recognition, emotion detection, storage in the database and calculations to find the positive (happy and surprise), negative emotion (sad, fear, angry, and disgust) and neutral (neither positive nor negative). For understanding the functioning of the model, OpenCV and CNN fundamentals have been explained in detail in the paper. This paper concludes by discussing the future scopes of the tool created. In the past, CCTV cameras were used for security only, but now these can be used to get customers’ real-time reviews also which will be very beneficial to them to improve their services. This will allow them to grow and compete in the future, where survival is going to depend on how well a business uses AI in its day-to-day operations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Prevention of Attacks in Vehicular Adhoc Networks

Prevention of Attacks in Vehicular Adhoc Networks

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2024 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2024

作者： Anjali, Thuvva Goyal, Rajeev G.n, Balaji Amity University Computer Science and Engineering Amity School of Engineering and Technology Gwalior India Vellore Institute of Technology Computer Science and Engineering School of Cse Vellore India

ISBN: (纸本)9798350348460

Over the past years, numerous methods have been developed to identify anomalies in traditional VANETs networks. A survey of VANET anomaly detection and mitigation methods is presented in this analysis. This survey looks into a variety of VANET research projects, attack types, anomaly detection methods, and mitigation strategies. VANETs provide wireless communication among vehicles as well as between vehicles and infrastructure. Its major objective is to improve road safety, comfort, and convenience. VANET varies from ad hoc networks due to its specific features. Several methods for identifying anomalies in conventional VANET networks have been developed over time. This work examines VANET anomaly detection and prevention technologies. Various VANET research studies, different types of attacks, anomaly detection, and VANET protection measures. The current investigation seeks to address various sorts of vehicle network assaults as well as existing security methods for coping with these attacks. This work will help academics understand the taxonomy of automotive network security vulnerabilities, which can subsequently be researched further to develop unique solutions. © 2024 IEEE.

关键词： Identity Based Signature Intelligent Transport System Intrusion Detection System Vehicle to Vehicle Vehicular Adhoc Network

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Probabilistic Forecasting Prediction Model for Anticipating Days with Elevated Air Pollution 5th

Probabilistic Forecasting Prediction Model for Anticipating ...

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5th International Conference on Computing, Communications, and Cyber Security, IC4S 2023

作者： Singh, Divya Singh, Shikha Hazela, Braham Singh, Vineet Department of Computer Science and Engineering Amity School of Engineering and Technology Lucknow Amity University Uttar Pradesh Lucknow India

ISBN: (纸本)9789819725496

Public health and the environment are both threatened by air pollution. For prompt responses and public awareness, accurate air pollution forecasting is essential, especially on days with high ozone levels. With a focus on ground ozone concentrations, the objective of this study is to develop a probabilistic forecasting model in Python. Using machine-learning algorithms and meteorological information like wind speed and outdoor temperature, the possibility of an ozone day is predicted. Python packages like Pandas, NumPy, and Scikit-Learn are used for implementation and assessment. The results demonstrate the effectiveness of the developed probabilistic forecasting models, with significant improvements over baseline configurations. The most promising configuration is found, demonstrating the power of ensemble approaches and parameter fine-tuning. The Brier skill score of the gradient boosting method shows the best results. The ensemble model’s performance is evaluated using Brier skill scores and compared to a naive prediction model. According to the results the gradient-boosting ensemble model has the best BSS of 0.119546. The importance of probabilistic forecasting in handling the complexity of air pollution prediction is emphasized. This research develops probabilistic forecasting approaches for air pollution prediction, which improves both environmental management and public health. Despite the challenges faced by the complexity of air pollution, the findings help enhance air pollution prediction. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Air pollution

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Glaucoma Classification Using Improved Pretrained Model 12th

Glaucoma Classification Using Improved Pretrained Model

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12th International Conference on Soft Computing for Problem Solving, SocProS 2023

作者： Singh, Piyush Bhushan Singh, Pawan Dev, Harsh Chaurasia, Brijesh Kumar Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Uttar Pradesh Lucknow India Department of Computer Science and Engineering Pranveer Singh Institute of Technology Kanpur India

ISBN: (纸本)9789819731794

The most common cause of blindness in the world is glaucoma. It can lead to a decline in eyesight and quality of life if not addressed within the stipulated time. In computer vision, convolutional neural networks (CNNs) have achieved a viable solution. The most standard glaucoma screening method is fundus imaging due to the compromises it makes between mobility, size, and price. In this paper, we utilized the RIM-1 DL dataset in two different versions: RIM-1 Hospital and RIM-1 Randomly. To enhance the image quality and increase accuracy, we used median filtering pre-processing techniques in this work. We also used fundus images to automatically diagnose glaucoma using six different Image-net-trained models (DenseNet121, DenseNet169, VGG19, InceptionV3, ResNet50, and MobileNetV2). The six CNN architectures mentioned above are modified using normalization, inception, and global pooling layers in the model with the pre-trained classification models. Results indicate that the DenseNet-121 is the most accurate model in this work, improving accuracy in the RIM-1 Hospital dataset from 70.68 to 80.13 and in the RIM-1 randomly generated dataset from 79.31 to 87.67 after the models were fine-tuned. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Neural network models

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Object Detection Using TensorFlow 2 and Amazon SageMaker

Object Detection Using TensorFlow 2 and Amazon SageMaker

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International Conference on Recent Developments in Cyber Security, ReDCySec 2023

作者： Goel, Vartika Arora, Deepak Rizvi, Sheenu Department of Computer Science & Engineering Amity School of Engineering and Technology Lucknow Amity University Uttar Pradesh Noida India

ISBN: (纸本)9789819998104

Many frameworks with packaged pre-guided models have been created to give users fast access to transfer learning considering the rapidly expanding field of object detection techniques. For instance, three well-known computer vision systems with trained models are GluonCV, Detectron2, and the Object Detection API for TensorFlow, as well. The TensorFlow2 Object Detection API is an update to the TensorFlow Object Detection API. One of the cutting-edge object identification algorithms that can be trained using the TensorFlow2 Object Detection API is EfficientDet from Google Brain (Implemented here). Authors created and implemented an EfficientDet model with the help of TensorFlow Object Detection API using Amazon SageMaker. It is constructed on top of TensorFlow 2, which facilitates its creation, training, and deployment. Because it is designed on top of TensorFlow 2, creating, training, and deploying object detection models is simple. SageMaker is a completely managed tool that lets data scientists and developers quickly build, direct, and implement ML models. To make it simpler to create high-quality models, SageMaker takes the labour-intensive tasks out of each stage of the ML process. Transfer learning on numerous pre-guided models accessible in TensorFlow Hub is made possible by object detection with TensorFlow in SageMaker. The head of the TensorFlow model that handles object detection is replaced based on the amount of class labels present in the guiding data. Based on fresh guiding data, either the entire network—including pre-guided model—or just the top layer (object recognition head) can be fine-tuned. Authors trained using a smaller dataset in this transfer learning method. Authors have talked over each step-in detail, including data collection and labelling with Ground Truth, making, and converting the data to TFRecord format, training as well as launching a special object detection model with the TensorFlow Object Detection API, and ultimately deploying th

关键词： Object detection

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Early Detection of Cognitive Skill Impairments using Machine Learning 8

Early Detection of Cognitive Skill Impairments using Machine...

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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Patil, Sunita Kukreja, Swetta Amity University Maharashtra Amity School of Engineering and Technology Department of Computer Science & Engineering Maharashtra Mumbai410206 India

ISBN: (纸本)9798350391770

Cognitive skills are essential for everyday tasks, encompassing mental abilities such as memory, problem-solving, and logical thinking. Conditions such as depression, anxiety, and schizophrenia can impair these skills, affecting memory, attention, and problem-solving abilities. The COVID pandemic and other stress-inducing events have a great impact on individuals, often leading to stress-related diseases. Depression often stems from heightened stress levels, yet individuals may struggle to recognize or seek help due to social stigma. Delayed treatment impairs outcomes. Surveys indicate low success rates in treating cognitive skill impairment. Early identification through routine cognitive testing is crucial, especially for vulnerable individuals due to age, family history, or health conditions. Regular screenings facilitate proactive healthcare management, leading to improved outcomes in patients with cognitive skill impairments. This study explores the application of Support Vector Machine (SVM) algorithms for the early detection of cognitive skill impairments, aiming to develop accurate prediction models for identifying individuals at risk of cognitive decline. By employing feature selection methods, the SVM achieved an 83% accuracy rate. This study aimed to advance the development of efficient cognitive assessment tools, enabling early intervention and personalized care for individuals vulnerable to cognitive impairment. © 2024 IEEE.

关键词： Support vector machines

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Eye Disease/Disorder Diagnosis Using Deep Learning 8th

Eye Disease/Disorder Diagnosis Using Deep Learning

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8th International Conference on Information and Communication technology for Intelligent Systems, ICTIS 2024

作者： Rastogi, Ishaan Singh, Shrey Tripathi, Suryansh Mittal, Mukund Bhulania, Paurush Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Noida Uttar Pradesh Noida India

ISBN: (纸本)9789819766772

Web-based interfaces for medical diagnostics and ophthalmology are being transformed by recent advances in web development. By properly analyzing medical pictures, particularly retinal imaging and fundus photos, convolutional neural networks (CNNs) and machine learning are revolutionizing illness prediction in optics. Precision, recall, and F1-score are essential measures for assessing the efficiency of models. The MERN stack (MongoDB, Express, React, and ***) distinguishes out in the development of websites for its flawless technology integration. ***, a crucial component, makes UI creation easier by emphasizing user experience improvement above peak performance with its effective Virtual DOM. *** selection is validated by its simple training arc, robust support from the community, and extensive guides, which make it easier to switch from more traditional frontend components. The influence that CNNs and transfer learning have on ophthalmology, as well as the effectiveness of the MERN stack in developing websites, are highlighted in this abstract’s conclusion. The need of precise medical evaluation and efficient interfaces for users is emphasized by these advances, which show great potential in developing both professions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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Crime Data Analysis 8th

Crime Data Analysis

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8th International Conference on Information and Communication technology for Intelligent Systems, ICTIS 2024

作者： Srivastava, Divyanshi Jha, Ujjwal Kumar Bhulania, Paurush Department of Computer Science Engineering Amity School of Engineering and Technology Amity University Noida Uttar Pradesh Noida India

ISBN: (纸本)9789819766772

The number of criminal cases in India is growing quickly, which is also causing an increase in the backlog of pending cases. The persistent rise in criminal cases is making it more challenging to categorize and resolve them. It’s critical to identify a location’s trends of criminal activity in order to stop it from occurring. If the agencies responsible for solving crimes have a clear understanding of the trends in criminal activity in a certain area, they will be able to perform their jobs more effectively. This can be achieved by applying various algorithms and machine learning techniques to identify trends in the criminal activity within a specific region. This study expedites the categorization of criminal cases and moves forward appropriately by forecasting the sorts of crimes in a certain location using a crime dataset. Because they are inefficient and slow-moving, traditional crime-solving approaches cannot keep up with the present fast-rising crime rate. Therefore, it would lessen the load on police and aid in crime prevention if we could figure out how to precisely forecast crime before it happens or create a "machine" that can support police officers. It is advantageous to use computer vision algorithms and techniques as well as machine learning (ML) to accomplish this. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Crime

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NeurDB: an AI-powered autonomous data system

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science China(Information sciences) 2024年第10期67卷 129-150页

作者： Beng Chin OOI Shaofeng CAI Gang CHEN Yanyan SHEN Kian-Lee TAN Yuncheng WU Xiaokui XIAO Naili XING Cong YUE Lingze ZENG Meihui ZHANG Zhanhao ZHAO School of Computing National University of Singapore College of Computer Science and Technology Zhejiang University Department of Computer Science and Engineering Shanghai Jiao Tong University School of Information Renmin University of China School of Computer Science and Technology Beijing Institute of Technology

In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and selfdriving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.

关键词： AI$\times$DB in-database AI intelligent data system

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