Unsupervised and nonparametric detection of information flows

Authors:
Jinsub Kim;Lang Tong
Affiliations:
School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853, United States;School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853, United States
Venue:
Signal Processing
Year:
2012

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Abstract

The problem of detecting the presence of possibly bidirectional and time-varying information flows through two nodes in a network is considered. Only the transmission timing measurements are used in the detection. The proposed technique assumes no parametric flow model and requires no training data. The consistency of the detector is established for a class of non-homogeneous Poisson traffic. The proposed detector is tested in a simulation using LBL TCP traces (Paxson and Floyd, 1995 [24]) and an experiment involving MSN VoIP sessions.