Page 54 - Trust in ICT 2017

1 Trust in ICT

With respect to trust provisioning in health care services and applications, the paper [22] presents the
importance of inclusion of trust into the development of software systems. Furthermore they have identified
that several factors should be considered in the process of software development.
There are a number of recent papers which aim to incorporate security engineering into mainstream
software engineering. Yet, capturing trust and security requirements at an organizational level, as opposed
to an Information Technology (IT) system level, and mapping these into security and trust management
policies is still an open problem. In this regard, [23] discuss a set of concepts founded on the notions of
ownership, permission, and trust and intended for requirements modelling. It also extends Tropos, an agent-
oriented software engineering methodology, to support security requirements engineering. These concepts
are formalized and are shown to support the automatic verification of security and trust requirements using
Data log. To make the discussion more concrete, they have illustrate the proposal with a Health Care case
study.
Related to smart grid applications, [24] discusses the trust management toolkit, which is a robust and
configurable protection system augmentation, which can successfully function in the presence of an
untrusted (malfunctioning) smart grid (i.e., communication based, protection system nodes). The trust
management toolkit combines reputation based trust with network flow algorithms to identify and mitigate
faulty smart grid protection nodes. The toolkit assigns trust values to all protection nodes. Faulty nodes,
attributed to component or communication system malfunctions (either intentional or unintentional), are
assigned a lower trust value, which indicates a higher risk of failure to mitigate detected faults.

Furthermore, [25] presents an approach for modelling user trustworthiness when traffic information is
exchanged between vehicles in transportation environments. Their multi-faceted approach to trust
modelling combines priority-based, role-based and experience-based trust, integrated with a majority
consensus model influenced by time and location, for effective route planning. The proposed representation
for the user model is outlined in detail (integrating ontological and propositional elements) and the algorithm
for updating trust values is presented as well.
Establishing trust relationships between peers is an essential approach to prevent threats. In P2P systems,
peers often interact with unknown or unfamiliar peers. P2P systems benefits highly from trust mechanisms
for a peer to decide whether another party is trustworthy by using the knowledge of others. In this regard,
[26] proposes a challenge response protocol to identify malicious or unreliable peers in P2P systems.

Nowadays, WSNs appear to be mature enough to be used by various applications. These applications rely on
trustworthy sensor data to control the processes. Related to this, [27] proposed a novel trust model for
sensor data during their entire life cycle. Capitalizing on subjective logic, they have implemented new design
operators for the combination and aggregation of opinions. Opinion on data is then used by applications for
further decision making.

Relevant same area, [28] has proposed a different approach for securing information aggregation in WSNs.
By extracting statistical characteristics from gathered information, this framework evaluates sensor nodes’
trustworthiness using an information theoretic metric. By employing unsupervised learning algorithm, the
framework can detect the compromised nodes. Moreover, with the help of the powerful Josang’s belief
model, the uncertainty existing in the sensory data and aggregation results is explicitly represented and
quantified. Compared with the conventional schemes that are based on cryptography schemes, the proposed
framework can effectively block the false data in the presence of multiple compromised nodes that would
bypass outlier detection.
6.2.7 Trust Management System

There have been many proposed trust management protocols for different types of networks such as
MANETs, WSNs, P2P networks and social IoT. The concept of “Trust” originally derives from social sciences
and is defined as the degree of subjective belief about the behaviours of a particular entity. [29] first
introduced the term ”Trust Management” and identified it as a separate component of security services in
networks and clarified that “Trust management provides a unified approach for specifying and interpreting
security policies, credentials, and relationships.”

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