This study develops an alternative methodology for the risk analysis of information systems security (ISS). an evidential reasoning approach under the Dempster-Shafer theory of belief functions. The approach has the following important dimensions. First, the evidential reasoning approach provides a rigorous, structured manner to incorporate relevant ISS risk factors, related countermeasures, an...

A new evidential reasoning based approach is proposed that may be used to deal with uncertain decision knowledge in multiple-attribute decision making (MADM) problems with both quantitative and qualitative attributes. This approach is based on an evaluation analysis model and the evidence combination rule of the Dempster-Shafer theory. It is akin to a preference modeling approach, comprising an...

This paper reports the application of an evidential reasoning approach to design selection of retro-fit options for complex engineering products. The particular selection problem investigated in this paper is initially modelled by means of techno-economic analysis and may be viewed as a multiple attribute decision making (MADM) problem with a hierarchical structure of attributes which may be me...

This paper presents an event modelling and reasoning framework where event-observations obtained from heterogeneous sources may be uncertain or incomplete, while sensors may be unreliable or in conflict. To address these issues we apply Dempster-Shafer (DS) theory to correctly model the event-observations so that they can be combined in a consistent way. Unfortunately, existing frameworks do no...

Nowadays ontologies present a growing interest in Data Fusion applications. As a matter of fact, the ontologies are seen as a semantic tool for describing and reasoning about sensor data, objects, relations and general domain theories. In addition, uncertainty is perhaps one of the most important characteristics of the data and information handled by Data Fusion. However, the fundamental nature...

In information driven MAS, information consumers collect information about their environment from various sources such as sensors. However, there is no guarantee that a source will provide the requested information truthfully and correctly. Even if information is provided only by trustworthy sources, it can contain conflicts that hamper its usability. In this paper, we propose to exploit such c...

Approximate reasoning with words is one of the remarkable human capability that manipulates perceptions in a wide variety of physical and mental tasks whether in fuzzy or uncertain surroundings. To model this remarkable human capability, L.A. Zadeh (1999) proposed a new concept of "computing with words", which is a methodology in which the objects of computation are words and propositions drawn...

Dempster-Shafer theory, which can be regarded as a generalisation of probability theory, is a widely used formalism for reasoning with uncertain information. The application of the theory hinges on the use of a rule for combining evidence from different sources. A number of different combination rules have been applied, each of which makes certain assumptions about the evidence. Here we describ...

We study the implication problem of measure-based constraints. These constraints are formulated in a framework for measures generalizing that for mathematical measures. Measures arise naturally in a wide variety of domains. We show that measure constraints, for particular measures, correspond to constraints that occur in relational databases, data mining applications, cooperative game theory, a...

In this work, we examine the problem of constructing and maintaining a map of an autonomous vehicle’s environment for the purpose of navigation, using evidential reasoning. The inherent uncertainty in the origin of measurements of sensors demands a probabilistic approach to processing, or fusing, the new sensory information to build an accurate map. In this paper, the map is based on a two-dime...