| Περίληψη: | This dissertation focuses on privacy as well as the technologies that can enhance
privacy in the context of applications that are part of a broader framework
for developing innovative e-Government services aimed at attracting citizens’
confidence. In order to eliminate the negative elements of today’s identification
methods that often lead to the disclosure of more information about the individual
than it is necessary, a new line of research has been developed in recent years to
create digital certificates based on the disclosure of selected user identity elements.
This research has led to the creation of the Attribute Based Credentials (ABCs)
which are digital certificates that allow their holders to disclose, selectively and
under their own control, only the information required by the service they wish
to use, without giving full details of their complete identity, thus protecting the
identity elements of the users and their privacy. These certificates can, therefore, be
the cornerstone of reliable, trustworthy, and at the same time secure applications
in which those involved (people and devices) can be partially identified without
compromising their privacy. Within this context, in this dissertation, we propose a
new business model for innovative e-Government applications (without limiting
the use of the model in this field) based on Collective Intelligence, focusing on
privacy technologies such as the ABCs. The goal is to describe a business model
for supporting applications for smart cities and services that people can trust
and, also, participate in their operation. More specifically, in the context of this
model, privacy preserving techniques are described to connect multiple computing devices and people aiming at the massive gathering of environmental parameters as well as their distributed storage and processing on people’s devices, in a way that respects the privacy of the participants (devices and people alike). Participants help, using the sensors on their mobile devices, in data collection related to their
ambient environment (e.g. temperature) or their behavior (e.g. movement). In
this way, applications can draw useful information after proper processing of the
sent information. Also, in the framework of this dissertation, a new mathematical
model is proposed for partial identity disclosure certificates and ABCs in particular
that allows the formulation of quantitative privacy level evaluation criteria that can
assess whether it is safe to disclose a subset of a person’s identity elements without (or with minimal) privacy loss. These criteria are based on the Bayes theory and conditional probabilities, leading to an approach of evaluating the privacy risk of revealing a set of identity elements to a service. Finally, the results of a survey are presented which aims at highlighting the issues and concerns inherent in the use of electronic identification methods in the Public Sector. The survey, also, reveals how these problems are addressed by public officials in view of the new ABCs technologies. The aim of this research is to strengthen the trust of Public Officials in the applications they use in their daily tasks to support the eGovernment vision.
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