Towards a Platform for Widespread Embedded Intelligence - ERCIM

SPECIAL THEME: Embedded Intelligence
information can then be combined with
the high-level information obtained from
our program source to provide a highly
accurate analysis that will give guaranteed
bounds on program execution time.
In order to produce convincing results, it
is necessary to test our approach using
sophisticated and realistic applications.
Researchers at the Laboratoire des
Sciences et Matériaux d'Électronique —
LASMEA (Clermont-Ferrand, France),
Adaptable and Context-Aware
Trustworthiness Evaluation
by Gabriele Lenzini, Santtu Toivonen and Ilkka Uusitalo
have been developing a number of realtime
computer vision algorithms in
Hume. These algorithms can be
exploited to detect, for example, road
features from a moving vehicle, an
essential component of any self-controlled
(autonomous) road vehicle. In
due course, we intend to apply these
algorithms to the sensor and control systems
used in the CyCab autonomous
vehicle (http://www.robosoft.fr), a selfcontrolled
electric car resembling a golf
Conducted as part of the EU-ITEA Trust4All project, which aims to enhance
dependability in networked and component-based systems, VTT Technical
Research Centre of Finland and Dutch Telematica Instituut began investigating
trustworthiness evaluation in ubiquitous environments. So far, the research has
concerned context-aware trust and trust evaluation with indirect information.
Trust is an increasingly important phenomenon
to grasp and support in open
environments, such as where networked
devices operate. A common scenario
sees a Trustor, the subject of trust, search
for a Trustee, the object of trust. The
Trustor's trustworthiness evaluation
directed to the Trustee should be facilitated.
Semi-automatic trustworthiness
evaluation is of special relevance in
embedded systems as well as in the
semantic web, or in the ubiquitous environments,
where the Trustors and
Trustees can be computer programmes
in addition to human beings. To perform
an appropriate evaluation, Trustors
request various information characterising
Trustees. Typical solutions ask for
users' trust credentials, often expressed
in terms of user profile, reputation, and
recommendations. The difference
between reputation and recommendation
here is that reputation is based on the
experiences of the Trustor, whereas recommendations
are communicated experiences
of others.
Contextual data, that is information considered
relevant to the interaction
between a Trustor and a Trustee,
including the environment in which this
46 ERCIM News No. 67, October 2006
interaction occurs, can influence the
result of the trust establishment. For
example, acting in a safe environment
can affect the trust that an application
has in a component. Context-awareness
has been recognised in many research
areas of information technology, such as
information filtering and retrieval, service
provisioning and communication.
However, the relationship between context
and trust has not received very much
attention, apart from some occasional
work. This is unfortunate, since such
relationship can easily be recognised and
its existence justified.
In the first phase of our research, we contextualise
trust-evaluation by considering
individual context attributes and
assign them with values influencing the
trustworthiness evaluation process.
Depending on the importance of a given
context attribute, determined by what we
call a trust purpose, weights can be
assigned to amplify or weaken the
respective attribute's influence on the
overall trust. For example, the Trustee's
location can have significant importance
when deciding if to grant access to the
local wireless network. A policy can be
introduced so that nobody (regardless of
buggy, and capable of speeds up to a
rather alarming 30 km/h.
Links:
Project: http://www.embounded.org
Hume: http://www.hume-lang.org.
Please contact:
Kevin Hammond, University of St Andrews,
Scotland, UK
E-mail: kh@dcs.st-and.ac.uk
possessing the network key or not) is
allowed to use it if residing outside the
company boundaries. We apply the
notion of context also to reputations and
recommendations. When dealing with
reputations and recommendations, contextual
data can be used to emphasise
other experiences that have taken place
under “similar enough” conditions to
those in which the Trustor currently
finds himself. Here “similarity” between
contexts can be computed, for example
based on reasoning or on context ontologies,
and expressed as minimal contextual
distance.
The above-mentioned trust evaluation
works on the assumption that reputation
data and recommendations are directly
available to the Trustor. In the second
phase of our research, we extended the
adaptability of context-aware trustworthiness
evaluation by considering scenarios
where this direct information is
not necessarily available to the Trustor.
In such cases, we highlight three subcases
to be studied. First, the Trustee's
behaviour in other contexts may be
unknown. Secondly, the Trustee's
behaviour in the current context may be
unknown, for example due to absence of
knowledge referring to the current context.
Thirdly, reliable recommenders
and/or recommendations about the
Trustee might not be available or they
could refer to the Trustee acting in different
context. We address each of these