Multi‐objective evolutionary approach to select security solutions. Issue 2 (25th April 2019)

• Record Type: Journal Article
• Authors: Lee, Yunghee; Choi, Tae Jong; Ahn, Chang Wook
• Is Part Of: CAAI transactions on intelligence technology. Volume 2:Issue 2(2017)
• Page Start: 64
• Page End: 67
• Publication Date: 2019-04-25
• Subjects: genetic algorithms -- Pareto optimisation -- evolutionary computation; multiobjective evolutionary approach -- efficient security solutions -- optimised security method -- security methods -- weakness decrease -- security issues -- NSGA‐II algorithm -- diverse solution; Artificial intelligence -- Periodicals; Computer science -- Periodicals; Artificial intelligence; Computer science; Electronic journals; Periodicals; 006.305
• DOI: 10.1049/trit.2017.0002
• Languages: English
• ISSNs: 2468-6557

Abstract

Abstract : 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.