Information security investment decision by fuzzy economics

The article derives fuzzy economic decision models to evaluate economic feasibility of information security investment. The Net Present Value (NPV), and discounted Return on Investment (ARoI) models are proposed for the execution of cost-benefit analysis. Since fuzzy results are in the form of a complex nonlinear representation, and do not always provide a totally ordered set in the same way that crisp numbers do, the current paper approximates the resulting fuzzy profitability indexes by a triangular fuzzy number initially, and then uses the Mellin Transform to obtain the means and variances of the triangle fuzzy numbers in order to determine their relative ranking in a decision-making process. The performances of the proposed fuzzy economic models are verified by considering their application to a practical illustration. These investigations not only confirm that the results of the fuzzy economic models are consistent with those of the conventional crisp models, but also demonstrate that the proposed models are more flexible, intelligent and computationally efficient compared to the traditional crisp engineering economics. The developed models represent readily implemented feasibility analysis tools for use in the arena of uncertain economic decision-making.