Design and Implementation of Post-Detection of Denial of Service (DoS) as a Mitigation System (PDDMS) Based on Dynamic Access Control List Algorithm

A. F. Rochim, Fahmi Maghrizal Mochtar, Adnan Fauzi
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Abstract

Computer networking maintenance and monitoring have been essential things. A human administrator could not monitor the whole resources for 24 hours and take action directly in inactive hours when an incident occurs. Automating the network appliance with the integration of an attack detection system could help solve the problem. This study mainly focuses on mitigating network attacks using the Dynamic Thresholding algorithm as a detection and mitigation system based on network automation using the Dynamic Access Control List algorithm. The data used for this research is self-generated in a virtual environment and a mitigation system written in Python to automate the router configuration through REST API. Prototype of the mitigation system, namely post-detection of DoS as a Mitigation System (PDDMS). The system testing phase results show that the mitigation system has an average of 1.57 seconds response time to configure ACL for one router. The implementation evaluated using Confusion Matrix shows 0% results of True-Positive Rate in the generated dataset, with 23.01% of accuracy and no positive results detected, which resulted in no response taken by mitigation system.
基于动态访问控制列表算法的DoS后检测缓解系统(PDDMS)设计与实现
计算机网络的维护和监控已经成为必不可少的事情。人工管理员无法在24小时内监视整个资源,并在事件发生时在非活动时间内直接采取行动。通过集成攻击检测系统来自动化网络设备可以帮助解决这个问题。本研究主要关注使用动态阈值算法作为基于动态访问控制列表算法的网络自动化的检测和缓解系统来缓解网络攻击。本研究使用的数据是在虚拟环境中自行生成的,并且是用Python编写的缓解系统,通过REST API自动化路由器配置。缓解系统的原型,即DoS检测后作为缓解系统(PDDMS)。系统测试阶段的结果表明,缓解系统对一台路由器配置ACL的平均响应时间为1.57秒。使用混淆矩阵评估的实施结果显示,在生成的数据集中,True-Positive Rate的结果为0%,准确率为23.01%,没有检测到阳性结果,这导致缓解系统没有采取响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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