Pedro A. Diaz-Gomez

A Genetic Algorithm Approach for Doing Misuse Detection in Audit Trail Files

This paper focuses on the development of an intrusion detection system based on genetic algorithms. We present and justify a fitness function independent of variable parameters that addresses the problem of false positives. This fitness function is a generic one that can be used for either off-line or online intrusion detection systems or it allows us consider pseudo intrusions, which could be used to prevent the occurrence of actual intrusions. The paper also describes extending the system to account for the fact that intrusions may be mutually exclusive and defines the union operator which greatly speeds the search for intrusions

Genetic Algorithms for Hunting Snakes in Hypercubes: Fitness Function Analysis and Open Questions

Hunting for snakes of maximum length in hypercubes has been addressed with non-heuristic methods for hypercubes of dimension less than eight. Above that dimension the problem is intractable because the search grows exponentially with the dimension, which make it an NP-hard problem. Heuristic methods, like genetic algorithms, have been used to solve this kind of problem. We propose different fitness functions to find snakes in hypercubes of dimension greater than three and pose some open questions regarding the number of maximum length snakes in a hypercube of dimension d

Three interconnected parameters for genetic algorithms

When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria, selection operator and pressure, and fitness function to be used in order to solve the problem. This paper tests a relationship between (1) crossover probability, (2) mutation probability, and (3) selection pressure using two problems. This relationship is based on the schema theorem proposed by Holland and reflects the fact that the choice of parameters and operators for genetic algorithms needs to be problem specific.

Analysis and mathematical justification of a fitness function used in an intrusion detection system

Convergence to correct solutions in Genetic Algorithms depends largely on the fitness function. A fitness function that captures all goals and constraints can be difficult to find. This paper gives a mathematical justification for a fitness function that has previously been demonstrated experimentally to be effective.