Genetic Algorithms for Role Mining Problem

The paper proposes a new approach to solve role mining problem in role-based access control systems. This approach is founded on applying genetic algorithms as heuristic optimization methods that are effectively used when the search space is too huge to be fully explored. To realize genetic algorithms, we propose some important novelties: having many chromosomes by individuals, presentation of genes as complex objects, dividing selection and mutation into several phases, accounting data confidentiality and availability in fitness functions and other. Proposed genetic algorithms were tested on randomly generated data sets for "basic" and "edge" role mining problems. The test results allow to assert that genetic algorithms may be successfully applied to efficiently solve main kinds of role mining problems.