Authors:
Faten Louati
1
;
Farah Barika Ktata
2
and
Ikram Amous
3
Affiliations:
1
MIRACL Laboratory, FSEGS, Sfax University, Sfax, Tunisia
;
2
MIRACL Laboratory, ISSATSo, Sousse University, Sousse, Tunisia
;
3
MIRACL Laboratory, Enet’com, Sfax University, Sfax, Tunisia
Keyword(s):
Intrusion Detection System, Big Data, Spark Streaming, Real Time Detection, Machine Learning.
Abstract:
Nowadays, Security is among the most difficult issues in networks over the world. The problem becomes more challenging with the emergence of big data. Intrusion detection systems (IDSs) are among the most efficient solutions. However, traditional IDSs could not deal with big data challenges and are not able to detect attacks in real time. In this paper, a real time data preprocessing and attack detection are performed. Experiments on the well-known benchmark NSL KDD dataset show good results either in terms of accuracy rate or time of both training and testing and prove that our model outperforms other state-of-the-art solutions.