Analysis of the vulnerability estimation and neighbor value prediction in autonomous systems

Abstract The security within autonomous systems (AS)s is one of the important measures to keep network users safe and stable from the various type of Distributed Denial of Service (DDoS) attacks. Similar to the other existing attack types Internet control message protocol (ICMP) based attacks are re...

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Main Authors: Nematullo Rahmatov, Faisal Saeed, Anand Paul
Format: Article
Language:English
Published: Nature Portfolio 2022-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-13613-3
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author Nematullo Rahmatov
Faisal Saeed
Anand Paul
author_facet Nematullo Rahmatov
Faisal Saeed
Anand Paul
author_sort Nematullo Rahmatov
collection DOAJ
description Abstract The security within autonomous systems (AS)s is one of the important measures to keep network users safe and stable from the various type of Distributed Denial of Service (DDoS) attacks. Similar to the other existing attack types Internet control message protocol (ICMP) based attacks are remained open challenge on the Internet environment. In this study, we have proposed a method to estimate the vulnerability of 600 AS provider edge (PE) routers by sending ICMP packets and predicted AS neighbor values using least square regression (LSR) approach. The results of our study show that 265 AS PE routers are vulnerable due to ICMP flood attack from the 600 ASs which were analyzed. Additionally, we have predicted that about 60% of total AS neighbors will be reduced in the next 3 years. Our results indicate that some ASs still did not deploy the firewall system in the boundary of their networks. Similarly, we also observed that the majority of ASs which expected to have less neighbor values in the next 3 years is due to change their routing paths to find adjacent paths.
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spelling doaj.art-36582cb3ddb2486b87068c65f994273e2022-12-22T03:21:58ZengNature PortfolioScientific Reports2045-23222022-06-0112111510.1038/s41598-022-13613-3Analysis of the vulnerability estimation and neighbor value prediction in autonomous systemsNematullo Rahmatov0Faisal Saeed1Anand Paul2School of Computer Science and Engineering, Kyungpook National University, DaeguSchool of Computer Science and Engineering, Kyungpook National University, DaeguSchool of Computer Science and Engineering, Kyungpook National University, DaeguAbstract The security within autonomous systems (AS)s is one of the important measures to keep network users safe and stable from the various type of Distributed Denial of Service (DDoS) attacks. Similar to the other existing attack types Internet control message protocol (ICMP) based attacks are remained open challenge on the Internet environment. In this study, we have proposed a method to estimate the vulnerability of 600 AS provider edge (PE) routers by sending ICMP packets and predicted AS neighbor values using least square regression (LSR) approach. The results of our study show that 265 AS PE routers are vulnerable due to ICMP flood attack from the 600 ASs which were analyzed. Additionally, we have predicted that about 60% of total AS neighbors will be reduced in the next 3 years. Our results indicate that some ASs still did not deploy the firewall system in the boundary of their networks. Similarly, we also observed that the majority of ASs which expected to have less neighbor values in the next 3 years is due to change their routing paths to find adjacent paths.https://doi.org/10.1038/s41598-022-13613-3
spellingShingle Nematullo Rahmatov
Faisal Saeed
Anand Paul
Analysis of the vulnerability estimation and neighbor value prediction in autonomous systems
Scientific Reports
title Analysis of the vulnerability estimation and neighbor value prediction in autonomous systems
title_full Analysis of the vulnerability estimation and neighbor value prediction in autonomous systems
title_fullStr Analysis of the vulnerability estimation and neighbor value prediction in autonomous systems
title_full_unstemmed Analysis of the vulnerability estimation and neighbor value prediction in autonomous systems
title_short Analysis of the vulnerability estimation and neighbor value prediction in autonomous systems
title_sort analysis of the vulnerability estimation and neighbor value prediction in autonomous systems
url https://doi.org/10.1038/s41598-022-13613-3
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