Title :
Towards intrusion detection by information retrieval and genetic programming
Author :
Kromer, Pavel ; Platos, Jan ; Snasel, Vaclav ; Abraham, Ajith
Author_Institution :
VSB - Tech. Univ. of Ostrava, Ostrava, Czech Republic
Abstract :
Fuzzy classifiers and fuzzy rules are powerful tools in data mining and knowledge discovery. In this work, intrusion detection is approached as a data mining task and genetic programming is deployed to evolve fuzzy classifiers for detection of intrusion and security problems. We train the fuzzy classifier on a data set modeled as a fuzzy information retrieval collection and investigate its ability to detect illegitimate actions. Proposed approach is experimentally evaluated on the popular KDD Cup intrusion detection data set.
Keywords :
data mining; fuzzy set theory; genetic algorithms; information retrieval; pattern classification; security of data; KDD Cup intrusion detection data set; data mining; fuzzy classifier; fuzzy rule; genetic programming; information retrieval; knowledge discovery; Biological cells; Genetic programming; Information retrieval; Intrusion detection; Query processing; Testing; Training;
Conference_Titel :
Information Assurance and Security (IAS), 2010 Sixth International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-7407-3
DOI :
10.1109/ISIAS.2010.5604063