چكيده به لاتين
Abstract
The ever-increasing popularity of the Internet and other communication and information technologies, has led to faster access to information and more effective information sharing. The advantages of such facilities are known to everybody, but the serious threats caused by them cannot be ignored too. One of such challenges is the problem of privacy violation of individuals. That is, many people who use information and communication tools, may disclose their private information to unauthorized people, consciously or unconsciously.
On the other hand, the rapid growth of such technologies has motivated researchers and practitioners to design some tools to provide users of systems and networks with privacy. Due to a number of reasons, none of these tools can guarantee the privacy of users in an absolute sense. Thus, in this thesis, we are investigating how we can quantify the usefulness of privacy-preserving methods. In fact, we are seeking an approach that enables us to measure the effectiveness of such methods. It is desirable to know how much they are successful in providing users with privacy, when operating in a hostile environment.
In this thesis, in order to deal with the aforementioned challenge, we propose a formal framework for the quantitative analysis of privacy in a variety of computation and communication environments. To the best of our knowledge, all methods proposed for the quantitative evaluation of privacy metrics are specific solutions to specific problems. The generality and completeness of the analysis framework make it outstanding among all proposed solutions in the field of privacy quantification. From completeness standpoint, it provides modeler with definitions and tools needed for the process of the quantitative analysis of privacy, ranging from privacy problem formulation to privacy metric evaluation. From generality standpoint, it makes it possible to formulate a wide variety of privacy problems and to evaluate many privacy metrics.
The quantitative analysis framework consists of two models: a privacy model and a quantitative evaluation model. The former is a conceptual model that is useful for formulating privacy problems. The latter is an analytical model that is useful for the definition and evaluation of privacy metrics. The usefulness of the framework is illustrated by applying it for formulating a number of privacy problems and obtaining a number of privacy metrics.
Keywords: Privacy, Analysis, Framework, Model, Quantification, Metric.
