| Abstract: | Soft computing continuously gains interest in many fields of academic and industrial domain; among
the most notable characteristics for using soft computing methodological tools is the ability to handle
with vague and imprecise data in decision making processes. Similar conditions are often encountered in
requirements engineering. In this paper, we introduce the PriS approach, a security and privacy requirements
engineering framework which aims at incorporating privacy requirements early in the system
development process. Specifically, PriS provides a set of concepts for modelling privacy requirements in
the organisation domain and a systematic way-of-working for translating these requirements into system
models. The conceptual model of PriS uses a goal hierarchy structure. Every privacy requirement is
either applied or not on every goal. To this end every privacy requirement is a variable that can take two
values [0,1] on every goal meaning that the requirements constraints the goal (value 1) or not (value 0).
Following this way of working PriS ends up suggesting a number of implementation techniques based
on the privacy requirements constraining the respective goals. Taking into account that the mapping
of privacy variables to a crisp set consisting of two values [0,1] is constraining, we extend also the PriS
framework so as to be able to address the degree of participation of every privacy requirement towards
achieving the generic goal of privacy. Therefore, we propose a fuzzification of privacy variables that maps
the expression of the degree of participation of each privacy variable to the [0,1] interval. We also present
a mathematical framework that allows the concurrent management of combined independent preferences
towards the necessity of a privacy measure; among the advantages of the presented extended
framework is the scalability of the approach in such a way that the results are not limited by the number
of independent opinions or by the number of factors considered while reasoning for a specific selection
of privacy measures. |
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