A collaborative intrusion detection system using log server and neural networks

Abstract

With the explosive rapid expansion of computer use during the past few years, security has become a crucial issue for modern computer systems. Today, there are so many intrusion detection systems (IDS) on the Internet. A variety of intrusion detection techniques and tools exist in the computer security community. We can easily download, install and configure them to our needs. But there is a potential problem involved with intrusion detection systems that are installed locally on the machines to be monitored. If the system being monitored is compromised, it is quite likely that the intruder will alter the system logs and the intrusion logs while the intrusion remains undetected. In this project KIT-I, we adopt remote logging server (RLS) mechanism, which is used to backup the log files to the server. Taking into account security, we make use of the function of SSL of Java and certificate authority (CA) based on key management. Furthermore, neural networks are applied in our project to detect the intrusion activities.