Open AccessMulti‐objective evolutionary approach to select security solutions
Author(s) -
Lee Yunghee,
Choi Tae Jong,
Ahn Chang Wook
Publication year - 2017
Publication title -
caai transactions on intelligence technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.613
H-Index - 15
ISSN - 2468-2322
DOI - 10.1049/trit.2017.0002
Subject(s) - variety (cybernetics) , scheme (mathematics) , genetic algorithm , computer science , set (abstract data type) , risk analysis (engineering) , computer security , mathematical optimization , mathematics , business , artificial intelligence , machine learning , mathematical analysis , programming language
In many companies or organisations, owners want to deploy the most efficient security solutions at a low cost. The authors propose a way of choosing the optimised security method from many security methods by multi‐objective genetic algorithm (GA) considering cost and weakness decrease in this study. The proposed system can find the best security methods in various aspects of security issues. This study uses the NSGA‐II algorithm, which has been authorised in a variety of fields, to provide a comparison with old GAs. Their scheme has increased the dominant area by more than 30% compared with the previous scheme and can provide a more diverse solution set.