Page 80 - Trust in ICT 2017

1 Trust in ICT

The benefit of this approach is that it permits the use of explicitly stated expectations, such as
contract clauses, in the decision about whether to trust. This approach needs not to be limited to
contracts; social norms can equally be considered. With this in mind, this type of approach may be
suitable for reasoning explicitly about the integrity of agents, as well as their competence, based on
past performance with respect to norms and contracts.
The model proposed by Smith and des Jardins addresses the decision problem of agents by
modelling interactions as Iterated Prisoner’s Dilemma games. These are a repeated variant of the
classic Prisoner’s Dilemma game (Axelrod and Hamilton), where the ‘players’ have a personal
incentive to behave in an untrustworthy way.

8.3.3 Implement a trust reasoner using rule languages [83]
Ontologies are formal definitions of concepts and the relationships between them. The Web Ontology
Language OWL 2 is a W3C Recommendation since 2009. It is based on Description Logics (DLs), a family of
knowledge representation formalisms. OWL 2 RL (Rule Language) reasoning systems allow for rule-based
reasoning. OWL 2 Query Language (QL) supports conjunctive query answering against large volumes of
instance data that is stored in relational database systems. OWL 2 EL aims at applications that employ large
ontologies.
A reasoner is a program that infers logical consequences from a set of explicitly asserted facts or axioms and
typically provides automated support for reasoning tasks such as classification, debugging and querying. For
OWL 2 EL, scalable implementations of dedicated reasoning algorithms are available. A question is whether
these implementations perform better on OWL 2 EL ontologies than traditional reasoning engines, which
have been designed for much more expressive languages. Sematic tableau algorithms can be highly
optimized, so that they are not necessarily outperformed by straightforward implementations of polynomial-
time algorithms.

Here are some prospective reasoners that we can use for trust.
CB (Consequence-based reasoner, University of Oxford) is an implementation of a reasoning procedure for
Horn Ontologies, i.e. SHIQ ontologies that can be translated to the Horn fragment of first-order logic. CB’s
reasoning procedure can be regarded as an extension of the completion-based procedure for EL++ ontologies
and works by deriving new consequent axioms. It is theoretically optimal for Horn SHIQ ontologies as well as
for the common fragment of EL++ and SHIQ.
FaCT++ (Fast Classification of Terminologies, University of Manchester) is the new generation of the OWL
DL reasoner FaCT. It supports OWL DL and a subset of OWL 2 that is more expressive than the ontologies in
other ontologies. FaCT++ is implemented in C++ and based on optimized tableaux algorithms.
HermiT (University of Oxford) can determine whether or not a given ontology is consistent and identify
subsumption relationships between concepts, among other features. HermiT is based on a “hypertableau”
calculus.

TrOWL (Tractable reasoning infrastructure for OWL 2, University of Aberdeen) is the common interface to
a number of reasoners. TrOWL Quill provides reasoning services over OWL 2 QL. TrOWL REL is an optimized
implementation of the CEL algorithm that provides reasoning over OWL 2 EL. It employs a syntactic
approximation from OWL 2 DL to OWL 2 EL to enable OWL 2 DL ontologies to be classified within polynomial
time [41]. This approximation is soundness-preserving but sacrifices completeness. To support full DL
reasoning, TrOWL allows for the use of heavyweight plugin reasoners, such as FaCT++, Pellet, HermiT and
RacerPro.

8.4 A reputation and knowledge based trust model and decision making mechanism

There are numerous trust solutions have been proposed for each environment (e.g. P2P, MAS, e-commerce,
etc.), in this section, it aims at developing a trust service platform that cooperates with applications and
services to for the trust in future social IoT environments.

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