Study of Detection of DDoS attacks in cloud environment Using Regression Analysis

IF 2.2 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Data Pub Date : 2021-04-05 DOI:10.1145/3460620.3460750
Arun Nagaraja, U. Boregowda, V. Radhakrishna
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引用次数: 6

Abstract

Distributed Denial of Service (DDoS) attacks in the cloud environment are not as simple as the same attacks which occur in the traditional physical network environment. Not only one single attack is affecting the cloud environment, where as there are multiple sources to affect the environment. DDoS attacks can be detected using the existing machine learning techniques such as neural classifiers. This paper discusses on the survey carried out on DDoS attacks in the cloud environment. Using Machine learning techniques results to detection of higher false positive rates. Some of the widely used methods are ANN, SVM, kNN, J48, Feature rank and Feature selection methods to detect DDoS attacks in the cloud environment. This paper reviews various studies related to detection of network attacks in network and cloud environments.
基于回归分析的云环境下DDoS攻击检测研究
云环境中的分布式拒绝服务(DDoS)攻击不像传统物理网络环境中的攻击那么简单。影响云环境的不仅仅是一个攻击,还有多个攻击源。可以使用现有的机器学习技术(如神经分类器)检测DDoS攻击。本文讨论了对云环境下DDoS攻击的调查。使用机器学习技术可以检测到更高的假阳性率。目前广泛使用的方法有ANN、SVM、kNN、J48、Feature rank和Feature selection等方法来检测云环境下的DDoS攻击。本文综述了网络和云环境下网络攻击检测的相关研究。
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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来源期刊
Data
Data Decision Sciences-Information Systems and Management
CiteScore
4.30
自引率
3.80%
发文量
0
审稿时长
10 weeks
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