iTAP: In-network Traffic Analysis Prevention using Software-Defined Networks
Abstract
Advances in layer 2 networking technologies have fostered the deployment of large, geographically distributed LANs. Due to their large diameter, such LANs provide many vantage points for wiretapping. As an example, Google’s internal network was reportedly tapped by governmental agencies, forcing the Web giant to encrypt its internal traffic. While using encryption certainly helps, eavesdroppers can still access traffic metadata which often reveals sensitive information, such as who communicates with whom and which are the critical hubs in the infrastructure.
This paper presents iTAP, a system for providing strong anonymity guarantees within a network. iTAP is network-based and can be partially deployed. Akin to onion routing, iTAP rewrites packet headers at the network edges by leveraging SDN devices. As large LANs can see millions of flows, the key challenge is to rewrite headers in a way that guarantees strong anonymity while, at the same time, scaling the control-plane (number of events) and the data-plane (number of flow rules). iTAP addresses these challenges by adopting a hybrid rewriting scheme. Specifically, iTAP scales by reusing rewriting rules across distinct flows and by distributing them on multiple switches. As reusing headers leaks information, iTAP monitors this leakage and adapts the rewriting rules before any eavesdropper could provably de-anonymize any host.
We implemented iTAP and evaluated it using real network traffic traces. We show that iTAP works in practice, on existing hardware, and that deploying few SDN switches is enough to protect a large share of the network traffic.
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BibTex
@INPROCEEDINGS{meier2017in-network,
isbn = {978-1-4503-4947-5},
doi = {10.1145/3050220.3050232},
year = {2017-04-03},
booktitle = {SOSR '17: Proceedings of the Symposium on SDN Research},
type = {Conference Paper},
author = {Meier, Roland and Gugelmann, David and Vanbever, Laurent},
keywords = {Anonymous communication; Wiretapping; SDN},
language = {en},
address = {New York, NY},
publisher = {Association for Computing Machinery},
title = {iTAP: In-network Traffic Analysis Prevention using Software-Defined Networks},
PAGES = {102 - 114},
Note = {Symposium on SDN Research (SOSR 2017); Conference Location: Santa Clara, CA, USA; Conference Date: April 3-4, 2017}
}Research Collection: 20.500.11850/166051