A Linear Genetic Programming Approach to Intrusion Detection

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{song:2003:gecco,

• author = "Dong Song and Malcolm I. Heywood and A. Nur Zincir-Heywood",
• title = "A Linear Genetic Programming Approach to Intrusion Detection",
• booktitle = "Genetic and Evolutionary Computation -- GECCO-2003",
• editor = "E. Cant{\'u}-Paz and J. A. Foster and K. Deb and D. Davis and R. Roy and U.-M. O'Reilly and H.-G. Beyer and R. Standish and G. Kendall and S. Wilson and M. Harman and J. Wegener and D. Dasgupta and M. A. Potter and A. C. Schultz and K. Dowsland and N. Jonoska and J. Miller",
• year = "2003",
• pages = "2325--2336",
• address = "Chicago",
• publisher_address = "Berlin",
• month = "12-16 " # jul,
• volume = "2724",
• series = "LNCS",
• ISBN = "3-540-40603-4",
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming, Real World Applications",
• URL = "http://users.cs.dal.ca/~mheywood/X-files/Publications/27242325.pdf",
• DOI = "doi:10.1007/3-540-45110-2_125",
• abstract = "Page-based Linear Genetic Programming (GP) is proposed and implemented with two-layer Subset Selection to address a two-class intrusion detection classification problem as defined by the KDD-99 benchmark dataset. By careful adjustment of the relationship between subset layers, over fitting by individuals to specific subsets is avoided. Moreover, efficient training on a dataset of 500,000 patterns is demonstrated. Unlike the current approaches to this benchmark, the learning algorithm is also responsible for deriving useful temporal features. Following evolution, decoding of a GP individual demonstrates that the solution is unique and comparative to hand coded solutions found by experts.",
• notes = "GECCO-2003. A joint meeting of the twelfth International Conference on Genetic Algorithms (ICGA-2003) and the eighth Annual Genetic Programming Conference (GP-2003)",

}

Genetic Programming entries for Dong Song Malcolm Heywood Nur Zincir-Heywood

Citations