trust for individuals and semantic web services on the semantic web
TRANSCRIPT
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Trust for individuals and Semantic Web Services on the
Semantic Web
Roushdat Elaheebocus
School of Electronics and Computer ScienceUniversity of Southampton
ABSTRACTTrust is considered crucial for the success of the Semantic Web. In
this paper, research works in this area have been analysed and
grouped into two categories, namely 'trust for individuals' also
referred to as a 'Web of trust' and 'trust for Semantic Web
Services'. Their strategies are compared and analysed. It has been
found that the two categories differ in their approach and rarely
take costs into consideration.
Keywordssemantic web, strategies, semantic, trust, provenance
1. INTRODUCTIONA Web where people and agents understand one another for better
cooperation, such is the vision of the Semantic Web described as
an extension of the original Web [1]. Similarly to the real world,
for cooperation to happen a certain level of trust is required
among the entities involved. The issue of trust is considered so
crucial, several researchers have argued that for the Semantic Web
to succeed, the issue of trust must be addressed [10, 13, 23].
There is no universal definition for trust with respect to the
semantic web but most of them revolve around the idea of aquantifiable level of belief entity A has in entity B, that B is
competent, will perform reliably to the expectation of A and the
latter accepts to be vulnerable to an acceptable level during a time
period and under specific circumstances [2, 3, 4].
According to Donovan, A. and Gil, Y. [4], in order to understand
the issue of trust in the context of the Semantic Web, one should
first look at the much bigger picture which goes back to computer
science. Research work on trust can therefore be broadly
classified into four main categories;policy-based, reputation-
based, general-models, trust in information resources.
Due to space limitation we will focus on the last one that is 'trust
in information resources' which in fact makes use of the other
three categories and is the most relevant to the Semantic Web.
Trust has been given due importance as shown in the semantic
cake diagram below:
Source: Berners-Lee, T. (2000). Semantic Web on
XML.[5]
The semantic web cake diagram above shows a dedicated layer for
trust at the top which can make use of the different layers
underneath to achieve a semantic web of trust through digital
signature , encryption and reasoning. As for applications and user
interfaces, they are then come on top of the trust layer. This
diagram further illustrates the semantic web as an extension of the
Web mentioned earlier.
2. TWO AREAS OF RESEARCHIt has been found that there are two main streams of research that
have emerged from the Semantic Web researchers' community:
'Trust among individuals' which revolves around the idea of a web
of trust [8] and 'Trust for semantic web services' in which users
who can be either humans or intelligent agents making use of
services and needing to have a way of determining the trust of
services.
According to O'Hara, K. et al [15], there are five main strategies
when tackling the issue of trust on the semantic web namely:optimism, pessimism, centralisation, investigation and transitivity
and five type of costs to be taken into consideration; operational,
opportunity, risk, deficiency, service payments. We therefore
intend to investigate to what extent O'Hara's observation has been
implemented.
2.1 Trust among IndividualsIf each web user is to store information about a group of web
users and share it with others, this will result in an effective way
of managing trust on the Web as argued in [8,10] which also
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clearly points out that providing security is not equivalent to trust.
This approach results in a Web of trust upon which subsequent
researchers have based themselves upon [9, 10, 11, 12, 13]. As a
result, each link between individuals can have trust value [2].
In [9], the Friend-Of-A-Friend (FOAF) ontology [14] is extended
with foaf:person to accommodate a trust value from a scale of 1-9,
9 being absolute trust and 1 corresponds to absolute distrust. The
interesting part is that trust is acknowledged to be not onlydependent on an individual but also the context. Thus, a trust
value for an entity can vary from context to context. Trust
between individuals having no prior interaction is computed using
an algorithm which has been used only for demonstrating the
concept instead of its efficiency. The possible usage of such a
system has been illustrated using a chat-bot which can be queried
by passing two email addresses as parameter, and the trust value
between them is returned. This works almost in a similar fashion
as a web service. And finally, trust value has been embedded in a
mail client as a new field to indicate the level of trust for each
recipient.
However, [9] has not been tested on a set of real data contrary to
[11] where a network of people was considered. In this case trust
and distrust have been considered separately. Another majoraspect that was neglected in [9] was the time factor.[11] derives
the importance of time validity from the real world whereby
relationships are built and maintained with time. Data from
Epinions (Epinions.com) was used, part of which was masked and
cross-examined with the system's trust inference to evaluate its
accuracy.
Similarly [10] has also used Epinions in addition to Bibserv to
illustrate their trust management system but has assumed that data
on the semantic web is in the form of logical assertions that are
consistent. This leads us to think that it is only when the Web is
completely 'semantic' that the system will perform optimally.
Logical calculus and probabilistic calculus are used to generate a
trust value considered to be a function of his/her (user's) trust in
the sources providing it
The use of the Bayesian decision theory which has its roots in
probability is also commonly used in trust evaluation [12, 13].
The trust evaluation mechanism proposed in [12] is claimed to be
implementable on any unstructured peer-to-peer network. Based
upon reputation gathered through interaction with peers, the
information can then be shared over the network to produce a
global rating. This approach has been evaluated through
simulations only unlike [9, 10].
According to [13], trust is a probabilistic interpretation and
therefore to have a higher accuracy, the combination of
information from a variety of sources is performed.
We find that when trust is considered for individuals, the
'transitivity' strategy [15] is used mostly. One aspect which hasbeen neglected in most of the research work above however is the
cost except for [13] in which three kinds of cost were taken into
account namely: operational, opportunity, service payments. It is
also important to note that all the works cited above have claimed
to provide personalised trust.
2.2 Trust for Semantic Web ServicesSemantic web services are accessible not only by people but also
through agents and for that purpose, semantic markup languages
from the DAML family were introduced [16]. However enabling
usage by agents is not enough and requires that the latter find
ways of determining whether a service can be trusted and if yes, to
what extent.
Modelling elements were added to the Web Service Modelling
Ontology (WSMO) in [20] to include information about trust.
Service providers do not publish their services to a third party
registry but instead, join a peer-to-peer network of registriesthemselves when they want to provide a service. This effectively
addresses the limitation caused by centralised matchmaking and
allows providers to retain control over their policies. The
language used in this system is known as PeerTrust described as a
language for trust negotiation that supports delegation, policy
protection and negotiation strategies [21] and is built upon the
rule layer of the semantic web cake [5].
Another language used is the Poof Markup Language (PML) in
[22] to provide justification for the result provided by a web
service. This is particularly important to enable agents to reason.
Expressed in OWL, PML is thus compatible with semantic web
services and clients. One example of its usage is demonstrated in
IWTrust [18] where it is used for providing additional information
about provenance on answers obtained from the web enabling abetter evaluation of trustworthiness.
Provenance is of specially high concern [17, 18, 19] when dealing
with web services . [19] describes a trust aware inference
framework and an ontology to represent associations of trust and
provenance. The overall system is in the form of a semantic web
service that evaluates trustworthiness of semantic association
from multiple sources.
We see a difference between trust in individuals where the
transitive approach is favoured compared to semantic web
services whereby a more investigative approach [15] is used since
provenance decreases the amount of uncertainty in a source. The
costs of such strategies are not really discussed in most of the
research considered for semantic web services.
3. CONCLUSIONTrust is indeed a crucial issue for the success of the semantic web.
There exists multiple heterogeneous strategies for tackling trust on
the semantic web that are often not inter-operable which is not
necessarily completely a bad thing since each may be appropriate
in specific contexts. As these strategies become more mature,
standards will emerge and the issue of interoperability will be
solved. However, research works tend to ignore the different costs
described in [15] which can result in some undesired effect when
deployed that may not be apparent in simulation or through
sample data.
Also, trust originates from social behaviour and most solutions for
trust on the semantic web take a solely technological approach.External disciplines such as sociology, law and other cognitive
sciences should be considered as well to have a better
understanding of trust and how to address it [6]. Web Science [7]
does exactly this and hopefully better solutions will come out of
this in the near future.
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