Maturity and deployment of incentive-based collaborative intrusion detection

Develop and empirically evaluate deployed, scalable intrusion-detection pipelines that use token-based or reward-based incentive mechanisms to align participant behavior in decentralized collaborative detection.

Background

The paper identifies incentive mechanisms as the least mature of the four functional roles assigned to blockchain in detection systems. The CyberNFTs proposal is described as largely conceptual, with rewards based on correctly identified intrusions.

Unlike the more developed federated-learning-integrity literature, the surveyed work does not contain a high-impact-venue example combining incentives with a deployed and evaluated detection pipeline. This leaves the practical effectiveness and security of incentive-based participation unresolved.

References

This remains largely conceptual in the surveyed literature; we did not find a high-impact-venue instance that combines incentive mechanisms with a deployed, evaluated detection pipeline at the scale of the FL-integrity work surveyed above, marking this as both the least mature and most open functional role.

— From Network Intrusion Detection to Blockchain-Backed Endpoint Detection and Response: Mapping the Landscape of Decentralized Detection-and-Response Architectures  (2610.01872 - Shahsavari et al., 1 Oct 2026) in Section 5.4, “Incentive Mechanisms”