Vulnerability Assessment in Heterogeneous Web Environment Using Probabilistic Arithmetic Automata

In the current scenario most of the business enterprises are running through web applications. But the major drawback is that they fail to provide a secure environment. To overcome this security issue in web applications, there are many vulnerability detection tools are available at present. But the...

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Main Authors: A. Moshika, M. Thirumaran, Balaji Natarajan, K. Andal, G. Sambasivam, Rajesh Manoharan
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9433582/
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spelling doaj-3b177019f1f748a6bbdeef4b3e9e2c8d2021-06-02T23:18:13ZengIEEEIEEE Access2169-35362021-01-019746597467310.1109/ACCESS.2021.30815679433582Vulnerability Assessment in Heterogeneous Web Environment Using Probabilistic Arithmetic AutomataA. Moshika0https://orcid.org/0000-0002-9668-654XM. Thirumaran1https://orcid.org/0000-0002-2210-1553Balaji Natarajan2https://orcid.org/0000-0003-0040-9271K. Andal3https://orcid.org/0000-0001-8664-8219G. Sambasivam4https://orcid.org/0000-0002-7407-4796Rajesh Manoharan5https://orcid.org/0000-0001-7095-625XDepartment of Computer Science and Engineering, Sri Venkateshwaraa College of Engineering and Technology, Puducherry, IndiaDepartment of Computer Science and Engineering, Pondicherry Engineering College, Puducherry, IndiaDepartment of Computer Science and Engineering, Sri Venkateshwaraa College of Engineering and Technology, Puducherry, IndiaDepartment of Computer Science and Engineering, Sri Venkateshwaraa College of Engineering and Technology, Puducherry, IndiaFaculty of Information and Communication Technology, ISBAT University, Kampala, UgandaDepartment of Computer Science and Engineering, Sanjivani College of Engineering, Kopargaon, IndiaIn the current scenario most of the business enterprises are running through web applications. But the major drawback is that they fail to provide a secure environment. To overcome this security issue in web applications, there are many vulnerability detection tools are available at present. But these tools are not proactive and consistent as it does not adapt to all kinds of recent updates and is unable to track new emerging vulnerabilities. For the long-term functioning of a business enterprise, statistical data with efficient analytics on vulnerabilities is required to enhance its security impacts. Predictive Analytics is a powerful solution to effectively arm the recent incident response to modern-day threats. Predictive Analytics provides a proactive and decision-making approach and insights into how well security programs are working. It can also help to identify problem areas and can warn about imminent or active attacks in heterogeneous web applications to enhance the former features and analyze the origin and pattern of the attack in a more effective manner. The pattern analyzed through research is given as an input to the Machine Learning techniques such as Deterministic Arithmetic Automata (DAA), Probabilistic Arithmetic Automata (PAA) to predict the probabilistic value as an output. From the obtained probabilistic values, we can detect the cause of an attack, prevent the heterogeneous web application of business enterprises from further impacts and find the penetration level of an attack from web application to web service.https://ieeexplore.ieee.org/document/9433582/Security analyticsDeterministic Arithmetic Automata (DAA)probabilistic arithmetic automata (PAA)heterogeneous web application
collection DOAJ
language English
format Article
sources DOAJ
author A. Moshika
M. Thirumaran
Balaji Natarajan
K. Andal
G. Sambasivam
Rajesh Manoharan
spellingShingle A. Moshika
M. Thirumaran
Balaji Natarajan
K. Andal
G. Sambasivam
Rajesh Manoharan
Vulnerability Assessment in Heterogeneous Web Environment Using Probabilistic Arithmetic Automata
IEEE Access
Security analytics
Deterministic Arithmetic Automata (DAA)
probabilistic arithmetic automata (PAA)
heterogeneous web application
author_facet A. Moshika
M. Thirumaran
Balaji Natarajan
K. Andal
G. Sambasivam
Rajesh Manoharan
author_sort A. Moshika
title Vulnerability Assessment in Heterogeneous Web Environment Using Probabilistic Arithmetic Automata
title_short Vulnerability Assessment in Heterogeneous Web Environment Using Probabilistic Arithmetic Automata
title_full Vulnerability Assessment in Heterogeneous Web Environment Using Probabilistic Arithmetic Automata
title_fullStr Vulnerability Assessment in Heterogeneous Web Environment Using Probabilistic Arithmetic Automata
title_full_unstemmed Vulnerability Assessment in Heterogeneous Web Environment Using Probabilistic Arithmetic Automata
title_sort vulnerability assessment in heterogeneous web environment using probabilistic arithmetic automata
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2021-01-01
description In the current scenario most of the business enterprises are running through web applications. But the major drawback is that they fail to provide a secure environment. To overcome this security issue in web applications, there are many vulnerability detection tools are available at present. But these tools are not proactive and consistent as it does not adapt to all kinds of recent updates and is unable to track new emerging vulnerabilities. For the long-term functioning of a business enterprise, statistical data with efficient analytics on vulnerabilities is required to enhance its security impacts. Predictive Analytics is a powerful solution to effectively arm the recent incident response to modern-day threats. Predictive Analytics provides a proactive and decision-making approach and insights into how well security programs are working. It can also help to identify problem areas and can warn about imminent or active attacks in heterogeneous web applications to enhance the former features and analyze the origin and pattern of the attack in a more effective manner. The pattern analyzed through research is given as an input to the Machine Learning techniques such as Deterministic Arithmetic Automata (DAA), Probabilistic Arithmetic Automata (PAA) to predict the probabilistic value as an output. From the obtained probabilistic values, we can detect the cause of an attack, prevent the heterogeneous web application of business enterprises from further impacts and find the penetration level of an attack from web application to web service.
topic Security analytics
Deterministic Arithmetic Automata (DAA)
probabilistic arithmetic automata (PAA)
heterogeneous web application
url https://ieeexplore.ieee.org/document/9433582/
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