Inferring Edge Existence from Noisy Data

This is the landing page for the NoisyNets project. This project includes a methodology (along with source code) for inferring the probability of network edges given a dataset of noisy edge observations. This set of tools was used to infer the topology of the Autonomous System (AS) Graph formed by the Internet routers running the Border Gateway Protocol, or BGP. The rest of this site includes documentation for using the open source software for network inference as well as additional information.

If this work is useful or relevant to ongoing research, we request that you please cite our original publication of the methodology that was published in Infocom 2022.

Leyba, K. G., Daymude, J. J., Young J. G., Newman, M. E. J., Rexford, F., & Forrest, S. (2022). Cutting Through the Noise to Infer Autonomous System Topology. IEEE INFOCOM.