Securing Application-Level Topology Estimation Networks: Facing the Frog-Boiling Attack

Oct 26, 2011

Download: MP4 Video Size: 446.8MB  
Watch on YouTube

Abstract

Peer-to-peer real-time communication and media streaming applications
optimize their performance by using application-level topology estimation
services such as virtual coordinate systems. Virtual coordinate systems allow
nodes in a peer-to-peer network to accurately predict latency between arbitrary
nodes without the need of performing extensive measurements. However, systems
that leverage virtual coordinates as supporting building blocks, are prone to
attacks conducted by compromised nodes that aim at disrupting, eavesdropping,
or mangling with the underlying communications.
Recent research proposed techniques to mitigate basic attacks (inflation, deflation,
oscillation) considering a single attack strategy model where attackers perform
only one type of attack. In this work we explore supervised machine learning
techniques to mitigate more subtle yet highly effective attacks (frog-boiling,
network-partition) that are able to bypass existing defenses. We evaluate our
techniques on the Vivaldi system against a more complex attack strategy model,
where attackers perform sequences of all known attacks against virtual coordinate
systems, using both simulations and Internet deployments.