Society is facing a critical shortage of professionals in cybersecurity, and the gap between supply and demand is increasing. The report "The Labor Market's Need for Digital Security Competence Towards 2030", prepared by NIFU on behalf of the Ministry of Justice and Public Security, estimates that the Norwegian labor market will still face a significant lacuna in 2030.
An important measure to meet this challenge is to promote continued education in the private and public sector by way of crisis management exercises. A well-designed and well executed exercise yields institutional learning and increases an organization's robustness and adaptability. Any realistic exercise is bound to be complex and involve several organizational levels. Typically it challenges operational and technical staff, management, and crisis teams on coordination, responsiveness, communication, and record keeping.
Alas, development is known to be costly and time-consuming, and the investment is weakened by the lack of well-studied methods for measuring learning and competence development over time. Therefore, the goal of the ASCERT project is to develop tools and methods that support a holistic approach to the design, execution, and evaluation of cybersecurity exercises. ASCERT is an interdisciplinary project that uses methods and results from symbolic and subsymbolic artificial intelligence, learning theory, and co-design. The goal is to reduce the costs associated with planning complex exercises, and at the same time develop learning principles and skill metrics to promote effective, longitudinal learning.
The project is a partnership between the Norwegian Computing Center, NTNU Cyber range, the Offshore directorate, EcoOnline crisis management, and the serious games company Levato. All results are developed in close cooperation between these partners to ensure that the solutions reflect real needs in the private and public sector.
Virkningene og effektene av prosjektet er tredelt. Første del består av kompetanseheving i fagmiljøene. Andre del er endring i høyere utdanning inne cybersikkerhet, hvor prosjektets resultater nå inngår i undeveisningen ved NTNU. Tredje del er knyttet til styrket beredskap og evnen til å håndtere kriser i organisasjoner som har deltatt i prosjektet.
According to the recent European Network and Information Security Agency (ENISA) report on cyber-security skills development, there is a 94 % increase in cybersecurity job postings in Europe since 2013, and it takes 20 % more time to fill those jobs compared to other IT jobs. This poses a major concern for both economic development and national security in the digital age. The development of highly effective cybersecurity training frameworks that ensure exceptional cybersecurity skills is in other words a fundamental prerequisite for the digital transformation of society.
Effective cybersecurity needs to span three organizational levels: (1) the strategic level, where societal services are subject to attacks and decisions are taken at an executive level; (2) the tactical level, where various parts of a National IT network are affected; (3) the operational level, where focus is on one concrete system. It is crucial to enhance cybersecurity skills at each level specifically as well as to coordinate training across levels.
The ASCERT project will develop an AI-supported architecture for cybersecurity training that 1) supports the design, execution and assessment of training scenarios across organisational levels, and that 2) incorporates skill-building principles and performance metrics to promote deliberate incremental learning.
Using attack-defence trees as a graphical user-facing representation, ASCERT will develop a formal semantics that translates such trees into AI planning languages for the purpose of generating and executing training scenarios. Based on case studies and interviews with domain experts, the project will build up a library of simple offensive and defensive moves annotated with additive metrics and skills to support automatic goal-based and skill-oriented scenario design. These library elements will then be mapped onto a multi-agent system on the NTNU Cyber Range to yield an integrated platform for simulation-based training.
