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Developing resilience and cyber-physical protection capabilities for critical aviation infrastructures
(2021-06-14) Lykou, Georgia; Λύκου, Γεωργία; Athens University of Economics and Business, Department of Informatics; Apostolopoulos, Theodoros; Stamatiou, Υannis; Μαυρίδης, Ιωάννης; Μάγκος, Εμμανουήλ; Κοτζανικολάου, Παναγιώτης; Στεργιόπουλος, Γεώργιος; Gritzalis, Dimitrios
Transport sector is a critical infrastructure that greatly supports the smooth functioning of society's welfare and viability of economies worldwide. Disruptions to transportation systems can cause large economic impacts or even human losses, so they should be adequately protected from physical and cyber-physical threats.We focused our research on aviation sector, which is the safest transport mode, however the most interdepended one in terms of information and communication technologies applied. Cyber-attacks are increasing in quantity and persistence, so the consequences of a successful malicious cyber-attack to civil aviation operations could be severe nowadays. Aiming to enhance operational practices and develop robust cybersecurity governance in smart airports, we have presented a systematic and comprehensive analysis of unlawful attacks towards smart airports, by implementing cybersecurity best practices and resilience measures.Our research examined cyber security challenges and interoperability in Air Traffic Management systems and proposed an extended threat model for analysing possible targets and risks involved. We analysed cyber resilience aspects in the aviation context and the need for holistic strategy of defence, prevention, and response. Furthermore, as the fastest growing segment of aviation, Unmanned Aerial Systems(UAS) continue to increase in technical complexity, and capabilities. However, UAS pose significant challenges in terms of safety, security, and privacy. An increasing phenomenon, nowadays, is drone-related incidents near airport facilities, which are expected to proliferate in frequency and severity, as drones become larger and more powerful. Critical infrastructures need to be protected from such aerial attacks, through effective counteracting technologies, risk management, and resilience plans. In this dissertation, we have explored how counter drone technologies can prevent, detect, identify, and mitigate rogue drones. We have analysed realistic attack scenarios of malicious drones’ attacks and proposed an effective C-UAS protection plan for each case. We have also discussed the applicability limitations of C-UAS in the aviation context and proposed a resilience action plan for airports stakeholders for defending airborne threats from misused drones.The integration of our research in the aviation sector, focused on air transport networks and introduced a risk-based method to analyse interdependencies and congestions in the aviation network. The proposed methodology and software tool can assess delay incidents in airports, produce weighted risk dependency graphs, presenting how a delay that occurred in one airport may affect the operational efficiency of other interconnected airports. The tool can also detect the most critical airports and congested connections, while it can indicate the n-order dependency chains, which should be avoided by airline flight planners, to reduce delay impacts in the aviation network.
A time-based risk analysis of cascading failures
(2014-12-31) Λύκου, Γεωργία; Lykou, Georgia; Athens School of Economics and Business, Department of Informatics; Gritzalis, Dimitrios
One of the most challenging problems in Critical Infrastructure (CI) protection is the assessment and mitigation of cascading failures across infrastructures. Dependency analysis is a computationally intensive problem and various models worldwide have been examined in this work, which have been proposed for evaluating potential cascading effects and cumulative security risk due to high-order dependencies between CIs. The problem intensifies when attempting a dynamic time-based dependency analysis. Further research is needed to examine how failure duration and contingency plans restoration time, can affect CIs protection and resilience. This thesis presents a time based extension of previous C.I. cascading effects and common-cause failure Risk Analysis models. The method assesses the risk arising from cascading failures, triggered by major or concurrent common-cause events, when Impact is evaluated by using a time-related, functional analysis, which takes into account the type of vulnerability and time performance of contingency plans. We employ different growth models, to capture slow, linear and fast evolving effects, but instead of using static projections, the evolution of each dependency is “objectified” by a fuzzy control system, which also considers the effect of near dependencies. To achieve this, the impact (and eventually, risk) of dependency is quantified on a time axis, into a form of many-valued logic. Furthermore, the methodology is extended by analyzing major failures triggered by common-cause cascading events, with the use of CIDA (Critical Infrastructure Dependency Analysis tool), which implements this extended risk-based methodology. CIDA aims to support decision makers to proactively analyze dynamic and complex dependency risk paths in two ways: (a) to identify potentially hidden dependencies of high impact and risk, before they are actually realized and (b) to simulate the effectiveness of alternative mitigation controls with different reaction time. New methodology results provided a sound and more accurate dynamic cascading risk analysis of interdependent CIs, showing that the use of time –based impact ranks is congruent with what is happening in real world outages or failures in CI operation.