Cyber- Threat Assessment for the Air Traffic Management System: A Network Controls Approach

Roy, Sandip; Sridhar, Banavar

doi:10.2514/6.2016-4354

Cited by 5 publications

(2 citation statements)

References 31 publications

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“…Building on these studies, a series of recent works have begun to assess the propagative impacts of traffic flow restrictions -whether due to cyber events, weather, or other causes (e.g. space vehicle operations) [16,18,19].…”

Section: Related Workmentioning

confidence: 99%

Cyber Threat Impact Analysis to Air Traffic Flows Through Dynamic Queue Networks

Tamimi

Hahn

Roy

2020

ACM Trans. Cyber-Phys. Syst.

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Air traffic control increasingly depends on information and communication technology (ICT) to manage traffic flow through highly congested and increasingly interdependent airspace regions. While these systems are critical to ensuring the efficiency and safety of our airspace, they are also increasingly vulnerable to cyber threats that could potentially lead to reduction in capacity and/or reorganization of traffic flows. In this paper, we model various cyber threats to air traffic control systems, and analyze how these attacks could impact the flow of aircraft through the airspace. To perform this analysis, we consider a model for wide-area air traffic based on a dynamic queuing network model. Then we introduce three different attacks (Route Denial of Service, Route Selection Tampering, and Sector Denial of Service) to the air traffic control system, and explore how these attacks manipulate the sector flows by evaluating the queue backlogs for each sector's outflows. Furthermore, we then explore graph-level vulnerability metrics to identify the sectors that are most vulnerable to various flow manipulations, and compare them to case-study simulations of the various attacks. The results suggest that Route Denial of Service attacks have a significant impact on the target sector and lead to the largest degradation to the overall air traffic flows. Furthermore, the impact of Sector Denial of Service attack impacts are primarily confined to the target sector, while the Route Selection Tampering impacts are mostly confined to certain aircraft.

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Section: Related Workmentioning

confidence: 99%

Cyber Threat Impact Analysis to Air Traffic Flows Through Dynamic Queue Networks

Tamimi

Hahn

Roy

2020

ACM Trans. Cyber-Phys. Syst.

Self Cite

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“…Studies [1] using Normal and Poisson distributions modelling constructed probability density functions based on 21-day raw flight delay data. An aggregate stochastic model [2] [3]based on Poisson processes was adopted to predict dynamic aircraft counts in regions of an airspace. In [4] [5], Eulerian models and aggregated traffic models were used instead to analyze delay characterizations based on flight delay data over two regions in U.S. airspace.…”

Section: Introductionmentioning

confidence: 99%

A Stochastic Characterization Based Data Mining Implementation for Airport Arrival and Departure Delay Data

2014

AMM

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The probabilistic distribution of Airport arrival and departure delays over a selected period of eight months was analyzed using an optimal Generalized Extreme Value (GEV) model in this paper. It is anticipated that quantitative stochastic characterizations of delay data out of our work would improve demand predictions in air traffic flow management systems. Analysis and verification through application of Beijing Capital International Airport’s history flight delay data demonstrate better Goodness of Fit of our optimal GEV based model.

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Threat impact analysis to air traffic control systems through flight delay modeling

Zeng

Wang

Tian

et al. 2021

Computers & Industrial Engineering

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Cyber- Threat Assessment for the Air Traffic Management System: A Network Controls Approach

Cited by 5 publications

References 31 publications

Cyber Threat Impact Analysis to Air Traffic Flows Through Dynamic Queue Networks

Cyber Threat Impact Analysis to Air Traffic Flows Through Dynamic Queue Networks

A Stochastic Characterization Based Data Mining Implementation for Airport Arrival and Departure Delay Data

Threat impact analysis to air traffic control systems through flight delay modeling

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