Framework for cloud intrusion detection system service
Nouf Saleh Aljurayban, Ahmed Emam · 2015
In this Internet era, the use of cloud computing is causing a massive volume of online financial transactions, and the exchange of personal and sensitive information over the internet. Attackers use many different types of malware in searches motivated by curiosity or financial gain. In this paper, we propose an efficient framework called the Layered Intrusion Detection Framework (LIDF) that can be applied on the different layers of cloud computing in order to identify the presence of normal traffic among the monitored cloud traffic. The proposed framework uses data mining, especially an Artificial Neural Network, which makes it accurate, fast, and scalable. At the same time, the LIDF can reduce the rate of the analyzed traffic and achieve better performance by increasing the throughput without affecting its main goal.