"Gads" A Dsr Approach To Designing Green Anomalie Detection Systems: Driving Security Into Ressource Efficiency

The rising demand for digital resilience calls for strong cybersecurity measures, e.g. real-time analytics and encryption. These security operations are essential for protection but have made security a significant factor in the energy use of digital infrastructure, yet these issues are often overlooked. This study addresses this gap by developing an adaptive green anomaly detection system (GADS) that balances security performance with environmental efficiency. Using a Design Science Research approach grounded in the Belief-Action-Outcome framework and Affordance Theory, GADS integrates sustainability considerations into all stages of the anomaly detection lifecycle. Through detection mechanisms and a governance layer, it enables organizations to identify and manage trade-offs between protection strength and energy consumption. Developed through three iterative design cycles combining theoretical synthesis, focus group sessions (N=16), and prototype evaluation, GADS contributes validated design principles for green cybersecurity, advancing the discourse on sustainable cybersecurity and extending Green Information System theory to security operations.