Neural Networks For Intrusion Detection And Its Applications

With rapid expansion of computer networks during the past decade, security has become a crucial issue for computer system. Different soft-computing based methods have been proposed in recent years for the development of intrusion detection system. Different neural network structures are analyzed to find the optimal neural network with regards to the number of hidden layers. Misuse detection is the process of attempting to identify instances of network attacks by comparing current activity against the expected actions of an intruder. Most current approaches to misuse detection involve the use of Rule- based expert systems to identify indications of known attacks. These techniques are less successful in identifying attacks which vary from expected patterns. Artificial neural networks provide the potential to identify and classify network activity based on limited, incomplete, and nonlinear data sources.