A Two Stage Method for Classifying the Cyber Attacks in Amazon Web Service Cloud By Machine Learning Techniques
Keywords:
Amazon web service , Machine learning, Multiclass support vector machine(MCSVM), Pattern Matching Algorithms.Abstract
In Modern digital world, security of our valuable information is always an essential issue. There may chances of deferent cyber attacks. Against these, IDS and many security techniques have been used. To obtain high detection rate and low false alarm rate the researchers also been used data mining techniques and other Machine Learning (ML) techniques. Machine learning is a type of artificial intelligence(AI) that provides computers with the ability to learn without being explicitly programmed.This paper proposed to classify the cyber attack in Amazon Web Service Cloud by using Multiclass SVM and Pattern Matching ML techniques.The system uses a two stage method for classification. The first stage classify the maximum number of attacks by using Multiclass SVM algorithm. The second stage is Pattern Matching to classify and prevent the remaining attacks. The existing ML techniques do not provide well processing of large data sets because of the network traffic. The Proposed method is an cloud based ML technique, which uses NSL KDD CUP99 dataset.The model is evaluated in terms of accuracy with the benchmark.
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