Structural Feature Based Anomaly Detection for Packed Executable Identification - Computational Intelligence in Security for Information Systems - page 272

Evaluating User-Centered Privacy Model (UPM)
in Pervasive Computing Systems

Ali Dehghantanha 1 , Nur Izura Udzir 2 , and Ramlan Mahmod 2

1 Faculty of Computing and Technology- Asia-Pacific University College of
Technology and Innovation, Kuala Lumpur, Malaysia
Ali [e-mail]
2 Faculty of Computer Science and Information Technology, University of Putra
Malaysia, Kuala Lumpur, Malaysia
{ izura,ramlan } @fsktm.upm.edu.my

Abstract. The fact that pervasive systems are typically embedded and
invisible makes it dicult for users to know when, where, and how these
devices are collecting data. So privacy is a major issue for pervasive
computing applications and several privacy models have been proposed
for pervasive environments. In this paper we present the evaluation of
a XML based User-centered Privacy Model (UPM) and measure this
model unobtrusiveness and discuss privacy policies' expressiveness, and
user control over private information. We show that the model provides
content, identity, location, and time privacy with low unobtrusiveness
while privacy policies are highly expressive and support mandatory and
discretionary rules, context sensitivity, uncertainty handling, and conflict
resolution.

Keywords: Privacy, Pervasive Computing, Privacy Evaluation.

1 Introduction

Providing users with enough privacy level is a basic requirement in pervasive
systems which provide services seamlessly everywhere, at any time for all the
users.
Different evaluation methods have been proposed for security and privacy in
pervasive computing systems. Ranganathan et al [1] proposed a benchmark for
pervasive computing systems which considered three characteristics for privacy
models as follow:

1. User control over private information which is the model ability to provide
content, identity, and location privacy.
2. Unobtrusiveness of privacy mechanisms which is the percentage of time user
consumes on interacting with privacy sub-system.
3. Expressiveness of privacy policies which is the policys ability to support
mandatory and discretionary rules, context sensitivity, uncertainty handling,
and conflict resolution.