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The science

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Secure data sharing and computing of ATM data

A new paradigm to protect private data while also enabling relevant computation.

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The Science

SecureDataCloud fosters interactions and secure data sharing among stakeholders by dint of secure multi-party computation techniques.

The project

SecureDataCloud is a research project funded by SESAR-WPE (Long Term Research) that presents an innovative solution to the data sharing challenge within ATM, pursuing collaborative knowledge creation among stakeholders while guaranteeing necessary levels of data privacy.

About secure multi-party computation

Secure Multi-party Computation (SMC) is a set of techniques and algorithms that allows two or more untrusted parties to perform some kind of computation on a data set, while keeping their respective information private. Once the computation is complete the only new information each party would possess is the output of that computation, without any additional knowledge on the information provided by the other party.

In other words, instead of providing a party with the full set of data (and thus creating a security issue) or alternatively denying access to the data (essentially blocking any possibility of using the data), the data owners could allow a third party to run computations on their data for some functions, without real access to the full dataset.

SMC in air transport

As any other socio-technical system, the air transport system is always looking for ways of improving its operations: SESAR in Europe, NextGen in USA, OneSky in Australia, SIRIUS in Brazil, or CARATS in Japan. One priority is shared among all of them: a free flow of information between the agents and stakeholders involved in the operation. Some examples span from sharing future trajectory plans by aircraft, negotiations for slot exchange by airlines, the continuous monitoring of global mobility and CO2 emissions, or achieving higher safety levels.

Achieving such seamless flow of information comes with notable challenges. Most ATM datasets are considered confidential and sensitive and, therefore private – both for their commercial value, and for the political or social consequences some of the analyses may cause. If stakeholders remain isolated with little cross-integration, the solutions being developed by the community, such as SESAR’s System Wide Information Management (SWIM), would not successfully and fully address this confidentiality issue, as data are actually released to the party requiring them. Essentially the confidentiality of the system is as good as the confidentiality of the worst procedure implemented by the entities.

A completely different approach is enabled by SMC. Parties can collectively compute on private data, with the security that the information will not be disclosed to the other participants. In fact, only the final result will be disclosed. Example includes airport slot trading, CO2 allowance trading, analysis of delay and safety reports, and many more!

Publications