Near-Deterministic Inference of AS Relationships

Abstract

This paper aims to improve on existing methods by providing a near-deterministic inference scheme (ND-ToR ) for solving the ToR problem. The input for ND-ToR is the Internet Core, a sub-graph that consists of the globally top-level providers of the Internet and their interconnecting links with their already inferred relationship types. Theoretically, given an accurately classified core, the algorithm deterministically infers most of the remaining AS relationships using the AS-level paths relative to this core, without incurring additional inference errors. In real-world scenarios, where the core and AS-level paths can contain errors (due to misconfigurations or measurements mistakes), the algorithm introduces minimal inference mistakes. We show that ND-ToR has relaxed requirements from the core, and proves to be robust under changes in its definition, size and density.