Visible to the public A graph-based evidence theory for assessing risk

TitleA graph-based evidence theory for assessing risk
Publication TypeConference Paper
Year of Publication2015
AuthorsSantini, R., Foglietta, C., Panzieri, S.
Conference Name2015 18th International Conference on Information Fusion (Fusion)
Date Publishedjul
Keywordscyber-physical layers, Electronic mail, epistemic uncertainty management, fuzzy set theory, fuzzy theory, graph representation, graph theory, graph-based evidence theory, heterogeneous sources, Internet, knowledge based systems, power grid, power grids, pubcrawl170107, pubcrawl170108, reduced power set, risk assessment, risk evaluation, risk management, rule-based systems, security, security of data, Uncertainty

The increasing exploitation of the internet leads to new uncertainties, due to interdependencies and links between cyber and physical layers. As an example, the integration between telecommunication and physical processes, that happens when the power grid is managed and controlled, yields to epistemic uncertainty. Managing this uncertainty is possible using specific frameworks, usually coming from fuzzy theory such as Evidence Theory. This approach is attractive due to its flexibility in managing uncertainty by means of simple rule-based systems with data coming from heterogeneous sources. In this paper, Evidence Theory is applied in order to evaluate risk. Therefore, the authors propose a frame of discernment with a specific property among the elements based on a graph representation. This relationship leads to a smaller power set (called Reduced Power Set) that can be used as the classical power set, when the most common combination rules, such as Dempster or Smets, are applied. The paper demonstrates how the use of the Reduced Power Set yields to more efficient algorithms for combining evidences and to application of Evidence Theory for assessing risk.

Citation Keysantini_graph-based_2015