12, July 2021

ESA Open Invitation to Tender: 1-10907
Open Date: 07/07/2021 10:11 CEST
Closing Date: 20/08/2021 13:00 CEST

The objective is to study the machine learning algorithms that would be most suitable tosupport ESA in monitoring the security events generated in representative environments tothose employed in their operational systems.Machine learning has rapidly emerged as a preferred technology for commercial Security Information Event Management (SIEM) and Security Orchestration, Automation Response (SOAR) providers in the monitoring of security events, but the algorithms involved usually require a significant amount of manual customization in order to avoid false positivesor false negatives. The unique environments created by ESA programmes and missions remain largely unexplored and under analyzed. Thus, this work aims to study the optimal types and set of algorithms that could be:automatically trained (unsupervised);manually trained (supervised); or trained through a combination of unsupervised and supervised learning; and rapidly deployed and used in the most complex space infrastructure environments Specifically, this activity will:1.Study and understand the amount and types of events generated in a complex spaceinfrastructure environment;2. Identify and characterize a baseline set of machine learning algorithms that would addressthe amount and types of events identified in task 1;3. Propose a dataset representing the theoretical magnitude and nature of the eventsproduced by a large-scale, complex ESA programme environment;4. Develop a real-time customizable generator capable of providing the proposed dataset;5. Tailor and evaluate the machine learning algorithms based on the generated dataset.The primary benefits of the work are foreseen to include both the consolidation of themachine learning algorithms suitable to meet the operational need to monitor security events,as well as a test dataset for that could both be used to support current and future ESA research,programmes, and missions. The outcome of this work may also potentially synergize well with other Machine Learning and Security research currently underway within ESA.Participation in the project would offer Slovak entities: the opportunity to familiarize themselves with the unique environments seen in ESA programmes, network with ESA experts that work on these issues, and potentially help to prepare the selected Slovak company to participate in future studies or product development opportunities that may arise.Finally, the activity will offer greater familiarity with the working practices of the Agency and the use of applicable space standards (ECSS).

Estabilishment: ESTEC
ECOS Required: No
Classified: No
Price Range: 100-200 KEURO
Authorised Contact Person: Sandy Chana Courtois
Initiating Service: TEC-ESS
IP Measure: N/A
Prog. Reference: E/0908-09 – PECS Slovakia
Tender Type: Open Competition
Open To Tenderers From: SK
Technology Keywords: 9-B-II-Automation, Autonomy and Mission Planning Concepts

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