This paper addresses the problem of creating patterns that can be used to model the normal behavior of a given process. The models can be used for intrusion-detection purposes. First, we present a novel method to generate input data sets that enable us to observe the normal behavior of a process in a secure environment. Second, we propose various techniques to derive either fixed-length or variable-length patterns from the input data sets. We show the advantages and drawbacks of each technique, based on the results of the experiments we have run on our testbed.
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Hardware and Architecture
- Computer Networks and Communications