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Global ATM Security Management

GAMMA is a project worth around fifteen million Euros which received co-funding from the European Union’s Seventh research and innovation Framework Programme (FP7) programme under grant agreement No 312382. The project stems from the growing need to address new air traffic management threats and vulnerabilities due, for instance, to the increased reliance on distributed enterprise computing and the automated flow of information across a ground and airborne network.

The goal of the GAMMA project is to develop solutions to emerging air traffic management vulnerabilities backed up by practical proposals for the implementation of these solutions. The project will also consider the new scenarios created by the Single European Sky programme.

RNC-Avionics attended the Final event for the project, hosted by Leonardo on the 15th November in Rome. During the Event the RNCA Attack Effect Prediction Module was demonstrated in integration with different prototypes. The module is designed as a decision support system which can collect and analysing the information received from different security systems (considered as event detectors). Based on the processed data, the system can produce the following information:

  1. Whether the system under attack.
  2. The type and target of the attack that is currently performed.
  3. Predictions of the further adversary actions and expected impact.

The analysis subsystem is designed as Dynamic Bayesian Network of Hidden Markov Model. Possible adversary actions are encoded as a graph model, similar to an attack tree modelling approach. Received events are considered as measurements in the Dynamic Model, allowing a sequential inference of the hidden variables to be performed. Hidden variables encode the attacker’s status, such as estimated skill, intentions, “position” within the system. Based on the estimated hidden state variables, a prediction of the adversary actions using Game Theory approach is performed, that estimates the expected target and impact.

Further details of the GAMMA project can be found at the following link:

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