An Adaptive Distributed Denial of Service Attack Prevention Technique in a Distributed Environment

Author:

Riskhan Basheer1,Safuan Halawati Abd Jalil1,Hussain Khalid1,Elnour Asma Abbas Hassan2,Abdelmaboud Abdelzahir3ORCID,Khan Fazlullah4,Kundi Mahwish4

Affiliation:

1. School of Computing and Informatics, Albukhary International University, Alor Setar 05200, Keddah, Malaysia

2. Computer Science Department, Community College-Girls Section, King Khalid University, Abha 62529, Muhayel Aseer, Saudi Arabia

3. Department of Information Systems, King Khalid University, Abha 61913, Muhayel Aseer, Saudi Arabia

4. Computer Science Department, Abdul Wali Khan University, Mardan 23200, Pakistan

Abstract

Cyberattacks in the modern world are sophisticated and can be undetected in a dispersed setting. In a distributed setting, DoS and DDoS attacks cause resource unavailability. This has motivated the scientific community to suggest effective approaches in distributed contexts as a means of mitigating such attacks. Syn Flood is the most common sort of DDoS assault, up from 76% to 81% in Q2, according to Kaspersky’s Q3 report. Direct and indirect approaches are also available for launching DDoS attacks. While in a DDoS attack, controlled traffic is transmitted indirectly through zombies to reflectors to compromise the target host, in a direct attack, controlled traffic is sent directly to zombies in order to assault the victim host. Reflectors are uncompromised systems that only send replies in response to a request. To mitigate such assaults, traffic shaping and pushback methods are utilised. The SYN Flood Attack Detection and Mitigation Technique (SFaDMT) is an adaptive heuristic-based method we employ to identify DDoS SYN flood assaults. This study suggested an effective strategy to identify and resist the SYN assault. A decision support mechanism served as the foundation for the suggested (SFaDMT) approach. The suggested model was simulated, analysed, and compared to the most recent method using the OMNET simulator. The outcome demonstrates how the suggested fix improved detection.

Funder

King Khalid University

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference28 articles.

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