Robust synchronization for 2-D discrete-time coupled dynamical networks

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 IEEEIn this paper, a new synchronization problem is addressed for an array of 2-D coupled dynamical networks. The class of systems under investigation is described by the 2-D nonlinear state space model which is oriented from the well-known Fornasini–Marchesini second model. For such a new 2-D complex network model, both the network dynamics and the couplings evolve in two independent directions. A new synchronization concept is put forward to account for the phenomenon that the propagations of all 2-D dynamical networks are synchronized in two directions with influence from the coupling strength. The purpose of the problem addressed is to first derive sufficient conditions ensuring the global synchronization and then extend the obtained results to more general cases where the system matrices contain either the norm-bounded or the polytopic parameter uncertainties. An energy-like quadratic function is developed, together with the intensive use of the Kronecker product, to establish the easy-to-verify conditions under which the addressed 2-D complex network model achieves global synchronization. Finally, a numerical example is given to illustrate the theoretical results and the effectiveness of the proposed synchronization scheme.This work was supported in part by the National Natural Science Foundation of China under Grants 61028008 and 61174136, the International Science and Technology Cooperation Project of China under Grant No. 2009DFA32050, the Natural Science Foundation of Jiangsu Province of China under Grant BK2011598, the Qing Lan Project of Jiangsu Province of China, the Project sponsored by SRF for ROCS of SEM of China, the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

Dynamic cyber-incident response

Permission to make digital or hard copies of this publication for internal use within NATO and for personal or educational use when for non-profi t or non-commercial purposes is granted providing that copies bear this notice and a full citation on the first page. Any other reproduction or transmission requires prior written permission by NATO CCD COE.Traditional cyber-incident response models have not changed significantly since the early days of the Computer Incident Response with even the most recent incident response life cycle model advocated by the US National Institute of Standards and Technology (Cichonski, Millar, Grance, & Scarfone, 2012) bearing a striking resemblance to the models proposed by early leaders in the field e.g. Carnegie-Mellon University (West-Brown, et al., 2003) and the SANS Institute (Northcutt, 2003). Whilst serving the purpose of producing coherent and effective response plans, these models appear to be created from the perspectives of Computer Security professionals with no referenced academic grounding. They attempt to defend against, halt and recover from a cyber-attack as quickly as possible. However, other actors inside an organisation may have priorities which conflict with these traditional approaches and may ultimately better serve the longer-term goals and objectives of an organisation

FACS: A geospatial agent-based simulator for analyzing COVID-19 spread and public health measures on local regions

This is a preprint of an article to be published by Taylor & Francis in Journal of Simulation on [date of publication], available online: https://www.tandfonline.com/[Article DOI].”European Union Horizon 2020 research and innovation programme under grant agreement No 824115 and 80092

Conditional probability generation methods for high reliability effects-based decision making

Decision making is often based on Bayesian networks. The building blocks for Bayesian networks are its conditional probability tables (CPTs). These tables are obtained by parameter estimation methods, or they are elicited from subject matter experts (SME). Some of these knowledge representations are insufficient approximations. Using knowledge fusion of cause and effect observations lead to better predictive decisions. We propose three new methods to generate CPTs, which even work when only soft evidence is provided. The first two are novel ways of mapping conditional expectations to the probability space. The third is a column extraction method, which obtains CPTs from nonlinear functions such as the multinomial logistic regression. Case studies on military effects and burnt forest desertification have demonstrated that so derived CPTs have highly reliable predictive power, including superiority over the CPTs obtained from SMEs. In this context, new quality measures for determining the goodness of a CPT and for comparing CPTs with each other have been introduced. The predictive power and enhanced reliability of decision making based on the novel CPT generation methods presented in this paper have been confirmed and validated within the context of the case studies

A Markov Multi-phase Transferable Belief Model for Cyber Situational Awareness

eXfiltration Advanced Persistent Threats (XAPTs) increasingly account for incidents concerned with critical information ex ltration from High Valued Targets (HVTs). Existing Cyber Defence frameworks and data fusion models cannot cope with XAPTs due to a lack of provision for multi-phase attacks characterized by uncertainty and con icting information. The Markov Multi-phase Transferable Belief Model (MM-TBM) extends the Transferable Belief Model to address the multi-phase nature of cyber-attacks and to obtain previously indeterminable Cyber SA. As a data fusion technique, MM-TBM constitutes a novel approach for performing hypothesis assessment and evidence combination across phases, by means of a new combination rule, called the Multi-phase Combination Rule with con ict Reset (MCR2). The impact of MM-TBM as a Cyber Situational Awareness capability and its implications as a multi-phase data fusion theory have been empirically validated through a series of scenario-based Cyber SA experiments for detecting, tracking, and predicting XAPTs.10.13039/100010418-Defence Science and Technology Laboratory

Developing an eBusiness Strategy to Achieve Consumer Loyalty Through Exlectronic Channels

E-Business channels are presenting novel opportunities for small vineyards to target new online market segments, to communicate directly with the customer and side-step the main wine distributors who have traditionally blocked access to substantially wider markets. In the UK, where the majority of wine producers is heavily reliant on direct sales, understanding the role that eBusiness channels can play in the buyer behaviour process could be critical for building effective customer relationships and sales. This paper investigates how competitive advantage can be achieved through B2C channels