Title: A study on network security monitoring for the hybrid classification-based intrusion prevention systems
Authors: Oscar Rodas; Marco Antonio To
Addresses: Research Laboratory in Information and Communication Technologies, Universidad Galileo, Guatemala, Guatemala ' Research Laboratory in Information and Communication Technologies, Universidad Galileo, Guatemala, Guatemala
Abstract: The current state of network security has reached alarming levels of intrusions because of newer types of complex attacks. The network security landscape demands better network monitoring tools and processes to cope with these threats. Intrusion prevention systems (IPSs) are among the tools that provide a proactive approach to monitoring, analysing and mitigating ongoing attacks. Although IPSs are a valuable and needed asset for protection, their success is based on how well their intrusion detection and false positive rates are. In this work, we present a modern reliable, scalable and robust framework, which uses a classification-based hybrid IPS that can manage the processing of authentication logs from different IPSs in the network. Also, it provides the means to intervene in real time, mitigating ongoing attacks. Moreover, we show various scenarios emulated in Dockemu, which provides a smoother way for attack implementation in a controlled environment.
Keywords: intrusion detection; intrusion prevention systems; IPS reliability; scalabe IPS; classification-based hybrid IPS; MongoDB; Syslog; Dockemu; network security; authentication.
International Journal of Space-Based and Situated Computing, 2015 Vol.5 No.2, pp.115 - 125
Available online: 01 May 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article