Abstract:
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. However, 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. We present an
approach to the process of misuse detection that utilizes the analytical strengths of neural
networks, and we provide the results from our preliminary analysis of this approach.
Keywords: Intrusion detection, misuse detection, neural networks, computer security.
1. Introduction
Because of the increasing dependence which companies and government agencies have on their
computer networks the importance of......
Join Now or Login to view the rest of this paper.
Approximate Word Count: 4864
Approximate Pages: 19 (260 words per double-spaced page) |