Threat Assessment Model for information Environments (TAME)
Lead Participant:
UNIVERSITY OF HERTFORDSHIRE
Abstract
The “Threat Assessment Model for information Environments” (TAME) is a third-generation threat assessment methodology, initially developed for security assessments of payment systems. It specifies how to perform big-data analytics on cyber security related datasets.
TAME is based on the organisational analysis of the customer's business, using business-modelling techniques for understanding the vulnerability interrelationships of business-critical assets (tangible and intangible). This understanding is then coupled with situational awareness data for analysing the motivation, capability and opportunity of threat agents for attack. TAME then generates a comprehensive threat list.
The ultimate goal of TAME is to help decision makers decide what cyber security controls are necessary and where they should be applied, while ensuring and assuring regulatory compliance.
The proposal is to develop the methodology into a web-based cyber-security machine-learning platform, providing SMEs with an efficient, portable and scalable solution for self-assessing their critical threats.
The startup will be supported by the University of Hertfordshire with a view to ultimately delivering a spin out company in Q3-4 2018 that then develops commercially as part of the UK cyber security ecosystem.
TAME is based on the organisational analysis of the customer's business, using business-modelling techniques for understanding the vulnerability interrelationships of business-critical assets (tangible and intangible). This understanding is then coupled with situational awareness data for analysing the motivation, capability and opportunity of threat agents for attack. TAME then generates a comprehensive threat list.
The ultimate goal of TAME is to help decision makers decide what cyber security controls are necessary and where they should be applied, while ensuring and assuring regulatory compliance.
The proposal is to develop the methodology into a web-based cyber-security machine-learning platform, providing SMEs with an efficient, portable and scalable solution for self-assessing their critical threats.
The startup will be supported by the University of Hertfordshire with a view to ultimately delivering a spin out company in Q3-4 2018 that then develops commercially as part of the UK cyber security ecosystem.
Lead Participant | Project Cost | Grant Offer |
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Participant |
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UNIVERSITY OF HERTFORDSHIRE | ||
INNOVATE UK | ||
UNIVERSITY OF HERTFORDSHIRE |
People |
ORCID iD |
Christopher Gibbs (Project Manager) |