<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Todor Tagarev</style></author><author><style face="normal" font="default" size="100%">Nikolai Stoianov</style></author><author><style face="normal" font="default" size="100%">George Sharkov</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrative  Approach to Understand Vulnerabilities and Enhance the Security of  Cyber-Bio-Cognitive-Physical Systems</style></title><secondary-title><style face="normal" font="default" size="100%">18th European Conference on Cyber Warfare and Security, ECCWS 2019</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">bio-integrated systems</style></keyword><keyword><style  face="normal" font="default" size="100%">cyber security</style></keyword><keyword><style  face="normal" font="default" size="100%">Cyber-physical system</style></keyword><keyword><style  face="normal" font="default" size="100%">Decision-making</style></keyword><keyword><style  face="normal" font="default" size="100%">Hybrid threats</style></keyword><keyword><style  face="normal" font="default" size="100%">System of systems</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">4 -5 July 2019</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">European Conference on Information Warfare and Security, ECCWS</style></publisher><pub-location><style face="normal" font="default" size="100%">Coimbra, Portugal</style></pub-location><volume><style face="normal" font="default" size="100%">2019-July</style></volume><pages><style face="normal" font="default" size="100%">492-500</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Rapid technological advances provide numerous benefits to our ways of work and leisure, banking and transportation, delivery of products and health assistance. The increased interconnectedness among devices, people, networks, and systems, however, introduces a level of complexity surpassing the experience accumulated so far. While the security of communications, network and information systems can be considered a well-established discipline, the study of security of cyber-physical systems is fairly recent. Furthermore, the dependencies of live organisms, including humans, with integrated sensors and electronics, of perceptions and cognition, and variety of drones on influences from cyberspace have been subject of only few, mostly incidental studies. The interdependencies among cyber, physical, biological systems, and humans in situation assessment and decision-making roles create new potential vectors of attack by malicious actors. If exploited, they will lead to cross impact among domains that are usually studied separately. Authors from three Bulgarian institutions, combining research and policy-making experience, embarked on the task to elaborate a comprehensive cybersecurity research agenda. This paper presents their concept for an integrative approach to the exploration of &amp;lsquo;systems of systems.&amp;rsquo; The study is structured along five domains: communications and information systems and networks; cyber-physical system; bio-integrated systems; cognitive processes, i.e. the processes of shaping perceptions, assessing a certain situation and options and making decisions; and drones, remotely controlled or autonomous, the latter case being particularly reliant on advances in artificial intelligence. This paper outlines the problem of vulnerability of each of the five domains to influences from cyber space. Then it presents some advances in cross-domain understanding of vulnerabilities, supported by examples of cybersecurity studies, and provides the outlines of a corresponding, interdisciplinary research agenda, built around the concept of systems of systems. The authors conclude by predicting that the field of cybersecurity will be subject to considerable growth in coming years, requiring multi-and inter-disciplinary competencies and scientific support. &amp;copy; 2019, Curran Associates Inc. All rights reserved.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Georgi Pavlov</style></author><author><style face="normal" font="default" size="100%">Juliana Karakaneva</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">E-Models and Methods for Project Management in the Public Area</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">decision support systems</style></keyword><keyword><style  face="normal" font="default" size="100%">Decision-making</style></keyword><keyword><style  face="normal" font="default" size="100%">defence acquisition</style></keyword><keyword><style  face="normal" font="default" size="100%">e-payment</style></keyword><keyword><style  face="normal" font="default" size="100%">Life cycle management</style></keyword><keyword><style  face="normal" font="default" size="100%">procurement</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2003</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">11</style></volume><pages><style face="normal" font="default" size="100%">136-147</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The application of scientific and/or applied methods and models at each stage of the life cycle of projects, implemented by public organisations, is an important precondition for effective, efficient and transparent management. One way to create a relevant environment is to identify appropriate methods and models for decision-making in implementing such projects. One constructive approach to defining the usefulness of a method or a model is to constitute a matrix with rows describing the kinds of project activity (stage or phase) and columns relating to a particular method or model. The authors propose implementation of software agents that suggest, either automatically or upon request, a method or model appropriate to support decision-making in each project phase. Such advanced approach improves the capabilities of decision makers to understand the impact of a particular decision, to generate options and assess alternatives, thus improving decision-making capacity and transparency of the decision making process.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">H.T. Evans</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Formulation of Crisis Plans and Strategies</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">crisis management</style></keyword><keyword><style  face="normal" font="default" size="100%">crisis management strategy</style></keyword><keyword><style  face="normal" font="default" size="100%">crisis plans</style></keyword><keyword><style  face="normal" font="default" size="100%">critique</style></keyword><keyword><style  face="normal" font="default" size="100%">Decision-making</style></keyword><keyword><style  face="normal" font="default" size="100%">deliberate planning</style></keyword><keyword><style  face="normal" font="default" size="100%">immediate action</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2003</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2003</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">10</style></volume><pages><style face="normal" font="default" size="100%">39-42</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents a framework for corporate emergency response planning. It describes how a crisis management team should be organized and what the specific responsibilities of team members should be, with a special attention paid to companies with international presence. The requirements for situation assessment and decision-making are clearly identified.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">James Moffat</style></author><author><style face="normal" font="default" size="100%">Susan Witty</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Phase changes in Meta-modelling using the Fractal Dimension</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bayesian Decision-Making</style></keyword><keyword><style  face="normal" font="default" size="100%">Decision-making</style></keyword><keyword><style  face="normal" font="default" size="100%">Fractal Dimension</style></keyword><keyword><style  face="normal" font="default" size="100%">intelligent agent simulation model</style></keyword><keyword><style  face="normal" font="default" size="100%">meta-model</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2002</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2002</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">52-67</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We discuss in this paper the development of a meta-model of an intelligent agent simulation model. Such intelligent agent models consist of a number of entities called agents, which interact with each other. The nature of such interactions creates emergent behaviour. In conflict or peacekeeping situations, these agents correspond to the actors in the situation (the different force elements, for example). A meta-model is thus a mathematical abstraction of such a simulation, composed of two parts. For the first part, the fractal dimension of a force is introduced as a parameter measuring the emergent ability of such forces to cluster locally, corresponding to local decision-making by individual agents. For the second part we consider the mathematics of Bayesian Decision-Making as a meta-model for top down decision processes in such simulation models.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Plamena Andreeva</style></author><author><style face="normal" font="default" size="100%">George Georgiev</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Fuzzy Control Based on Cluster Analysis and Dynamic Programming</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Clustering algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">Decision-making</style></keyword><keyword><style  face="normal" font="default" size="100%">Dynamic programming.</style></keyword><keyword><style  face="normal" font="default" size="100%">fuzzy control</style></keyword><keyword><style  face="normal" font="default" size="100%">Knowledge Based Systems</style></keyword><keyword><style  face="normal" font="default" size="100%">Learning in Fuzzy Environment</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1999</style></year><pub-dates><date><style  face="normal" font="default" size="100%">1999</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">3</style></volume><pages><style face="normal" font="default" size="100%">91-107</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper focuses on fuzzy control of a class of nonlinear systems, which are characterized by model uncertainty and inequality model constraints. The associated Intelligent Information System (IIS) is designed to store the results from possible training made by an expert and distributed via network. The paper considers cluster analysis for such a system, based on Bezdek’s fuzzy cluster method (FCM). The proposed method is used to classify the input data and to extract the rules. 
An example of fuzzy control for autonomous mobile system in 3D space is explored and the results from the decision using the method of dynamic programming in fuzzy environment are shown. The synthesized algorithm guides an autonomous vehicle in 3D space which pursues an object and evades an obstacle. The fuzzy control is based on determination of a maximizing decision by using dynamic programming. The maximizing decision is defined as a point in the space of alternatives at which the membership function of a fuzzy decision attains its maximum value. The purpose of the presented algorithm is to demonstrate a fuzzy method for determination of the trajectory of the dynamic object.</style></abstract></record></records></xml>