Open Call - Autonomous Decision Making for Cyber Defence
A Contract Award Notice
by DEFENCE SCIENCE AND TECHNOLOGY LABORATORY
- Source
- Contracts Finder
- Type
- Contract (Products)
- Duration
- 0.5 year
- Value
- £952K
- Sector
- TECHNOLOGY
- Published
- 05 Nov 2021
- Delivery
- 04 Oct 2021 to 31 Mar 2022
- Deadline
- 13 Sep 2021 23:59
Concepts
Location
1 buyer
- Defence Science & Technology Laboratory Salisbury
1 supplier
- Frazer Nash Consultancy Dorking
Description
Under this open call, the Authority is seeking novel Artificial Intelligence (AI) and Machine Learning (ML) approaches for autonomous cyber defence decision making. Specifically, the Authority is interested in research that aims to: • Develop AI and ML based approaches for autonomous response options planning. This could include (but is not limited to) the application of reinforcement learning, adversarial machine learning, game theory etc. Response options could include (but are not limited to): implementation of technical mitigation measures; initiating actions to increase information veracity or certainty before implementing a mitigation response; or initiating actions to identify the cause of system failure in order to recover from it. • Develop multi agent approaches and architectures for cyber defence decision making. Key aspects include the trade-off between centralised and de-centralised agents, approaches for information sharing between agents, agent hierarchy and multi agent consensus. Note that this should focus on the interaction of machine agents and not the interaction of humans with machine agents. • Develop methods and approaches to evaluating the decisions generated by the agents to determine their effectiveness and impact.
Award Detail
1 | Frazer Nash Consultancy (Dorking)
|
CPV Codes
- 72231000 - Development of software for military applications
- 72244000 - Prototyping services
- 72262000 - Software development services
Indicators
- Contract is suitable for SMEs.
Other Information
30092021-SERAPIS_ARCD_Open_Call_v01-O - U48 Part 3 SIGNED-FINAL.pdf Actual Procurement Timescales Template.docx
Reference
- R1000166607
- CF 2af58016-74ea-4081-b659-c5b39081ae3e