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[2602.12825] Reliable Hierarchical Operating System Fingerprinting via Conformal Prediction
Summary
This paper presents a novel approach to Operating System fingerprinting using Conformal Prediction, addressing limitations in existing methods by introducing structured strategies for improved accuracy and reliability.
Why It Matters
With the increasing importance of network security, accurate OS fingerprinting is crucial. This research enhances traditional methods by incorporating uncertainty quantification, which can lead to better security measures and automated policy enforcement in network environments.
Key Takeaways
- Introduces two structured Conformal Prediction strategies for OS fingerprinting.
- Level-wise CP (L-CP) offers tighter prediction sets but may lead to inconsistencies.
- Projection-based CP (P-CP) ensures hierarchical consistency at the cost of efficiency.
- Both methods provide validity guarantees, addressing key limitations of traditional fingerprinting.
- Improved OS identification can enhance network security protocols.
Computer Science > Cryptography and Security arXiv:2602.12825 (cs) [Submitted on 13 Feb 2026] Title:Reliable Hierarchical Operating System Fingerprinting via Conformal Prediction Authors:Rubén Pérez-Jove, Osvaldo Simeone, Alejandro Pazos, Jose Vázquez-Naya View a PDF of the paper titled Reliable Hierarchical Operating System Fingerprinting via Conformal Prediction, by Rub\'en P\'erez-Jove and 3 other authors View PDF HTML (experimental) Abstract:Operating System (OS) fingerprinting is critical for network security, but conventional methods do not provide formal uncertainty quantification mechanisms. Conformal Prediction (CP) could be directly wrapped around existing methods to obtain prediction sets with guaranteed coverage. However, a direct application of CP would treat OS identification as a flat classification problem, ignoring the natural taxonomic structure of OSs and providing brittle point predictions. This work addresses these limitations by introducing and evaluating two distinct structured CP strategies: level-wise CP (L-CP), which calibrates each hierarchy level independently, and projection-based CP (P-CP), which ensures structural consistency by projecting leaf-level sets upwards. Our results demonstrate that, while both methods satisfy validity guarantees, they expose a fundamental trade-off between level-wise efficiency and structural consistency. L-CP yields tighter prediction sets suitable for human forensic analysis but suffers from taxonomic inconsisten...