PRECISE: AI-Supported Security Chaos Engineering Framework for Resilient Software-Intensive Systems

Purpose and goal:

PRECISE aims to strengthen the security and resilience of software-intensive systems and digital infrastructures. The project achieves this by developing an AI-supported security chaos engineering framework for experimenting the cybersecurity aspects of systems.

The project goals are to: (1) develop an AI-supported framework for chaos testing, focused on cybersecurity and resilience, (2) integrate the framework into DevSecOps, and (3) publish the framework as open source to increase its societal benefit. Expected results and effects:

The insights and best practices gained from implementing this project will be generalised and applied to other industries. Indeed, this project’s planned impact extends beyond its immediate partners and participants, potentially catalysing transitive change within the Swedish industrial sphere. Moreover, by openly sharing project outcomes, the project aims to contribute to Sweden’s ability in creating and leveraging resilient digital infrastructure and communication effectively, thus paving the way for a more secure digital future.

Approach and implementation: This project employs an iterative design science research methodology and includes seven major

activities (i.e., work packages): (1) requirement gathering and planning, (2) state of the art and regulation analysis, (3) framework design and analysis, (4) implementation and integration, (5) framework evaluation and refinement, (6) exploitation, and (7) project management/coordination and dissemination.