Advanced Hybrid Technique in Detecting Cloud Web Application's Attacks

被引:0
|
作者
Amar, Meryem [1 ]
Lemoudden, Mouad [1 ]
El Ouahidi, Bouabid [1 ]
机构
[1] Mohammed V Univ, IPSS, Rabat, Morocco
来源
MACHINE LEARNING FOR NETWORKING | 2019年 / 11407卷
关键词
Attack-detection; Cloud; IDS; Machine learning; Security; Similarities; LEARNING ALGORITHMS; SECURITY;
D O I
10.1007/978-3-030-19945-6_6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Recently cloud computing has emerged the IT world. It eventually promoted the acquisition of resources and services as needed, but it has also instilled fear and user's renunciations. However, Machine learning processing has proven high robustness in solving security flaws and reducing false alarm rates in detecting attacks. This paper, proposes a hybrid system that does not only labels behaviors based on machine learning algorithms using both misuse and anomaly-detection, but also highlights correlations between network relevant features, speeds up the updating of signatures dictionary and upgrades the analysis of user behavior.
引用
收藏
页码:79 / 97
页数:19
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