SEVERITY OF VULNERABILITIES IN FEATURES AND ITS COUNTERMEASURES TO ENSURE DATA SECURITY AND PERSONALIZED DATA SAFETY IN AN AUTONOMOUS DRIVING WEB APPLICATION WITH CLOUD STORAGE IN THE EU

An autonomous driving application, Risk Estimation with a Learning AI (RELAI) is a web application by Engineering Data Intelligence GmbH that is directly connected to a cloud system. The aim of the autonomous web application is to derive new variant-rich synthetic test scenarios through learning...

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Main Author: Brynner, Parir Elvis
Format: Final Year Project
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.23057 /
Published: Universiti Teknologi PETRONAS 2021
Subjects:
QA75 Electronic computers. Computer science
Online Access: http://utpedia.utp.edu.my/23057/1/TDB4104_softbound_BrynnerParirElvis_20173%20-%20TRIBAL%20Licks.pdf
http://utpedia.utp.edu.my/23057/
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spelling utp-utpedia.230572022-03-11T04:29:22Z http://utpedia.utp.edu.my/23057/ SEVERITY OF VULNERABILITIES IN FEATURES AND ITS COUNTERMEASURES TO ENSURE DATA SECURITY AND PERSONALIZED DATA SAFETY IN AN AUTONOMOUS DRIVING WEB APPLICATION WITH CLOUD STORAGE IN THE EU Brynner, Parir Elvis QA75 Electronic computers. Computer science An autonomous driving application, Risk Estimation with a Learning AI (RELAI) is a web application by Engineering Data Intelligence GmbH that is directly connected to a cloud system. The aim of the autonomous web application is to derive new variant-rich synthetic test scenarios through learning methods where models are developed and trained that generalise test scenarios. Nowadays, almost every software application development has been using cloud system support to improve their performance. Centralised databases have provided the websites the ease of retrieving necessary data from cloud services as well as storing sensitive information. Availability of data in the cloud for the web application is beneficial for many web applications but it poses risks by exposing data (especially personalised data) to web applications which might already have security loopholes in them. Similarly, use of virtualization for cloud system services might risk data when user runs the software application without knowing the reliability of the user’s interaction with the software application. Universiti Teknologi PETRONAS 2021-01 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/23057/1/TDB4104_softbound_BrynnerParirElvis_20173%20-%20TRIBAL%20Licks.pdf Brynner, Parir Elvis (2021) SEVERITY OF VULNERABILITIES IN FEATURES AND ITS COUNTERMEASURES TO ENSURE DATA SECURITY AND PERSONALIZED DATA SAFETY IN AN AUTONOMOUS DRIVING WEB APPLICATION WITH CLOUD STORAGE IN THE EU. Universiti Teknologi PETRONAS. (Submitted)
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Brynner, Parir Elvis
SEVERITY OF VULNERABILITIES IN FEATURES AND ITS COUNTERMEASURES TO ENSURE DATA SECURITY AND PERSONALIZED DATA SAFETY IN AN AUTONOMOUS DRIVING WEB APPLICATION WITH CLOUD STORAGE IN THE EU
description An autonomous driving application, Risk Estimation with a Learning AI (RELAI) is a web application by Engineering Data Intelligence GmbH that is directly connected to a cloud system. The aim of the autonomous web application is to derive new variant-rich synthetic test scenarios through learning methods where models are developed and trained that generalise test scenarios. Nowadays, almost every software application development has been using cloud system support to improve their performance. Centralised databases have provided the websites the ease of retrieving necessary data from cloud services as well as storing sensitive information. Availability of data in the cloud for the web application is beneficial for many web applications but it poses risks by exposing data (especially personalised data) to web applications which might already have security loopholes in them. Similarly, use of virtualization for cloud system services might risk data when user runs the software application without knowing the reliability of the user’s interaction with the software application.
format Final Year Project
author Brynner, Parir Elvis
author_sort Brynner, Parir Elvis
title SEVERITY OF VULNERABILITIES IN FEATURES AND ITS COUNTERMEASURES TO ENSURE DATA SECURITY AND PERSONALIZED DATA SAFETY IN AN AUTONOMOUS DRIVING WEB APPLICATION WITH CLOUD STORAGE IN THE EU
title_short SEVERITY OF VULNERABILITIES IN FEATURES AND ITS COUNTERMEASURES TO ENSURE DATA SECURITY AND PERSONALIZED DATA SAFETY IN AN AUTONOMOUS DRIVING WEB APPLICATION WITH CLOUD STORAGE IN THE EU
title_full SEVERITY OF VULNERABILITIES IN FEATURES AND ITS COUNTERMEASURES TO ENSURE DATA SECURITY AND PERSONALIZED DATA SAFETY IN AN AUTONOMOUS DRIVING WEB APPLICATION WITH CLOUD STORAGE IN THE EU
title_fullStr SEVERITY OF VULNERABILITIES IN FEATURES AND ITS COUNTERMEASURES TO ENSURE DATA SECURITY AND PERSONALIZED DATA SAFETY IN AN AUTONOMOUS DRIVING WEB APPLICATION WITH CLOUD STORAGE IN THE EU
title_full_unstemmed SEVERITY OF VULNERABILITIES IN FEATURES AND ITS COUNTERMEASURES TO ENSURE DATA SECURITY AND PERSONALIZED DATA SAFETY IN AN AUTONOMOUS DRIVING WEB APPLICATION WITH CLOUD STORAGE IN THE EU
title_sort severity of vulnerabilities in features and its countermeasures to ensure data security and personalized data safety in an autonomous driving web application with cloud storage in the eu
publisher Universiti Teknologi PETRONAS
publishDate 2021
url http://utpedia.utp.edu.my/23057/1/TDB4104_softbound_BrynnerParirElvis_20173%20-%20TRIBAL%20Licks.pdf
http://utpedia.utp.edu.my/23057/
_version_ 1741195901190275072
score 11.62408

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