基于云的分布式拒绝服务攻击的人工智能检测

Sabah Alzahrani, Liang Hong
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引用次数: 24

摘要

本研究提出一套侦测已知与未知分散式拒绝服务(DDoS)攻击的系统。该系统采用了两种不同的入侵检测方法:基于异常的分布式人工神经网络和基于签名的方法。Amazon公共云用于运行Spark,作为具有不同机器核心的快速集群引擎。实验结果表明,与基于签名和神经网络的方法相比,该方法的检测准确率和检测率最高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Distributed Denial of Service (DDoS) Attacks Using Artificial Intelligence on Cloud
This research proposes a system for detecting known and unknown Distributed Denial of Service (DDoS) Attacks. The proposed system applies two different intrusion detection approaches anomaly-based distributed artificial neural networks(ANNs) and signature-based approach. The Amazon public cloud was used for running Spark as the fast cluster engine with varying cores of machines. The experiment results achieved the highest detection accuracy and detection rate comparing to signature based or neural networks-based approach.
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