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分布式环境中的一种自适应分布式拒绝服务攻击预防技术

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

作者信息

Riskhan Basheer, Safuan Halawati Abd Jalil, Hussain Khalid, Elnour Asma Abbas Hassan, Abdelmaboud Abdelzahir, Khan Fazlullah, Kundi Mahwish

机构信息

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

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

出版信息

Sensors (Basel). 2023 Jul 21;23(14):6574. doi: 10.3390/s23146574.

DOI:10.3390/s23146574
PMID:37514868
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10383483/
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.

摘要

现代世界中的网络攻击十分复杂,在分散环境中可能难以被发现。在分布式环境中,拒绝服务(DoS)和分布式拒绝服务(DDoS)攻击会导致资源不可用。这促使科学界提出在分布式环境中的有效方法,以减轻此类攻击。根据卡巴斯基的第三季度报告,同步泛洪(Syn Flood)是最常见的DDoS攻击类型,在第二季度从76%上升到了81%。发起DDoS攻击也有直接和间接的方法。在DDoS攻击中,受控流量通过僵尸网络间接传输到反射器,以攻陷目标主机;而在直接攻击中,受控流量直接发送到僵尸网络,以攻击受害者主机。反射器是未被攻陷的系统,仅在收到请求时发送回复。为了减轻此类攻击,采用了流量整形和反击方法。同步泛洪攻击检测与缓解技术(SFaDMT)是我们用于识别DDoS同步泛洪攻击的一种基于自适应启发式的方法。本研究提出了一种识别和抵御同步攻击的有效策略。一种决策支持机制是所提出的(SFaDMT)方法的基础。使用OMNET模拟器对所提出的模型进行了模拟、分析,并与最新方法进行了比较。结果表明了所提出的修复方法如何提高了检测能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/5b6c392c0507/sensors-23-06574-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/b4dacb7d9a03/sensors-23-06574-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/56700efbc3d5/sensors-23-06574-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/604caef7ba94/sensors-23-06574-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/723776ec810f/sensors-23-06574-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/e820590d83da/sensors-23-06574-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/e871dc51f3d6/sensors-23-06574-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/dadd98d90add/sensors-23-06574-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/8a8023ff4b9d/sensors-23-06574-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33bd/10383483/5b6c392c0507/sensors-23-06574-g013.jpg

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