Situation awareness: new paradigm for the next generation infrastructures

SITUATION AWARENESS: NEW PARADIGM FOR THE NEXT GENERATION INFRASTRUCTURES

Adrian Gheorghe

Old Dominion University, Norfolk, VA, USA, adriangheorghe9145[AT]gmail.com

Sviatoslav Timashev

Ural Federal University, Ekaterinburg

Science and Engineering Center «Reliability and Safety of Large Systems and Machines» of the Ural Branch of the Russian Academy of Sciences, Ekaterinburg, timashevs[AT]gmail.com Critical infrastructure protection (CIP) and situation awareness (SA) currently are relevant topics in critical systems domain. The main concern in SA for Critical Infrastructures (CIs) has its roots in the particular structure of these, usually distributed, systems. CIs are interconnected and interdependent, and practically always include humans in the decision loop.

Most of the present approaches for SA in the field of CIP are based on using multisensory data fusion, and awareness is achieved by building a scenario of infrastructure predictive maintenance using data provided by CI sensors. In other words, instrumentally awareness is provided by diagnostics and monitoring systems, which become indispensable subsystems of every newly designed critical infrastructure system. The advent of the Internet of Things technology involves new ways of dealing and handling the emerging complexity of the interdependent CIs. The Internet of People networks will, in general, complicate the way how to address awareness strategies. To tackle these problems, new methods of regional risk management have to be developed and implemented in the frame work of regional governance.

Human interaction with the data fusion system and SA can be mainly regarded as the operator’s internal model of the state of the environment. Based on this representation, and additional high - level information, operators can assess the situation (risk, severity, possible consequences on other CIs, alternative scenarios, etc.) and decide any necessary actions. Using semi-automated continuous monitoring systems minimizes the risk of human error in a fast changing scenario of CI failure.

On the other side, automatic SA approaches often fail in handling both high level information and low level sensor fusion including the ability of providing possible alternative scenarios and evolution of an event. Moreover, common approaches are not able, due also to the lack of standard interchanging protocols and data representation, to use models that encompass both holistic representations and fine decompositions, and include human behavior. This is a vast new area of research.

The paper presents a holistic risk assessment methodology that implies assessing interdependencies of several CIs (at least three) in the presence of multiple sensors and human agents, in order to provide a decision making tool to upgrade security of the system of systems network.

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