Page 58 - Trust in ICT 2017

1 Trust in ICT

policies for data usage, depending on each data owner. The Data Manager used to work with IoT
data or resources from the infrastructure, and the Data Manager works with IoT applications.
• Application Layer: The layer contains end-user applications that receive the shared data from the
shared infrastructure.
The trust-based data usage mechanism allows benefits such as policy enforcement to share data based on
the properties of data consumers, allowing IoT shared platform to keep track of data usage history, and
more importantly allow data owners to monetize their data sharing by allowing them to dynamically
adjusting their policies on the fly.

6.4 Trust Provisioning in Architecture Domain
6.4.1 CT Ecosystem

Trust ontology and Trust model provisioning for social networks have been proposed for ICT ecosystem such
as [36]:

Friend-Of-A-Friend (FOAF) [37] represents a vocabulary and introduces an ontology for describing a web of
connected individuals. This ontology can serve as a tool to model and eventually create a network of society
of users by describing personal information about each person (realizing the node itself) and by describing
personal information regarding a set of users whom the user knows about (realizing the neighbours on the
network). Nodes on such a network are identified by their email address and email serves as their unique
identification.

• Jennifer Golbeck [38] introduces an ontology, that creates an important schema which extends FOAF
by using foaf:Person, giving the users this possibility to state and represent their trust in individuals
they know. Metric used to express trust is a value on the scalar range of 0-9, in which each scale
represents a trust level. These levels are set as properties under the domain of foaf:Person. These
levels correspond to: Distrusts absolutely, Distrusts highly, Distrusts moderately, Distrusts slightly,
Trusts neutrally, Trusts slightly, Trusts Moderately, Trusts highly, Trusts absolutely, according to
[38].
• Context was introduced as a property of trust. Trust is context-sensitive, as a result meaning and
semantics of trust can change depending on the context. This notion is represented in this ontology
under general trust or specific trust or topical trust, according to [38].
• Toivonen and Denker [39] study the trust in the context of communication and messaging. They
state that there are many factors which can have immense impact on the honesty and
trustworthiness of the messages we send and receive. The context-sensitivity of trust has been
realized and taken into account in their work. The work focuses on drastic changes that many issues,
namely reputation, credibility, reliability, trustworthiness and honesty could have, and how they
affect the progress of establishing and grounding trust, according to [41]. As a result of the work
being done, a set of ontologies have been defined to capture context-sensitive messaging and trust.
An ontology is developed to capture and denote the role of context-related properties and
information. This ontology captures the domain of message communication and exchange and
describes how the context information is actually attached to the messages. This ontology is
constructed mainly to visualize how trust is related to message and communication.
• Proof Markup Language’s trust Ontology Inference web [40] at Stanford University, has built a
semantic web-enabled knowledge platform and infrastructure. This platform is designated to help
users on the network to exploit the value of semantic web technologies in order to give and get trust
ratings to and from resources on the web. This process is referred to as justification of resources.
Proof Markup Language (PML) contains a term set for encoding the justifications and is designated
to work in a question answering fashion. PML is designated to help software agents to filter the
resources on the web of semantics by proof checking them and justifying the credibility of these
resources, on behalf of the users.
• With respect to metrics used for presenting the trust computational values and modelling the
mathematical notion of trust, there exist two approaches: presenting a trust metric with discrete

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