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Re: Non-source routing (was "failures during the preparation phase")

From: Pedro Moreno Sanchez <pmorenos@purdue.edu>
Date: Wed, 23 Mar 2016 21:41:56 -0400
To: <public-interledger@w3.org>
Message-ID: <56F345E4.4080108@purdue.edu>

my name is Pedro Moreno-Sanchez and I am a PhD student at the computer
science department at Purdue. My current research focuses on security
and privacy issues on credit networks. Moreover, I will be doing an
internship at Ripple this summer. Thus, I hope I can use this
opportunity to meet some of you there and discuss the interesting things
that are going on in this group.

I would like to bring to your attention a (non-source) routing approach
called landmark routing [1]. In a nutshell, this approach calculates a
path between a sender and a receiver through an intermediary node called
landmark. The idea behind this approach is to calculate the shortest
path (i.e., Breadth-First Search) from the landmark to every other node
and vice versa, from every node to the landmark. Then, a payment path
from sender to receiver can be reconstructed as sender -->other nodes
--> landmark --> other nodes ---> receiver. Vismanath et al.[2] have
shown that landmark routing performs much faster than other routing
approaches (e.g., using max-flow) in credit networks.

Given the similarities between a credit network and the ILP settings, it
might be worth it discussing this approach here. Moreover, as part of my
research, I have studied whether it is possible to use landmark routing
to build a credit network with privacy preserving payments. This is
challenging not only because of possible privacy leaks while calculating
payment paths but also due to privacy leaks during the calculation of
the available credit in a path.

To overcome these challenges, we designed a system called PrivPay [3], a
credit network system that uses a privacy-enhanced version of landmark
routing to perform privacy preserving payments. More recently, we have
designed a privacy-preserving credit network system with which we show
that it is possible to enforce strong privacy guarantees as we did with
PrivPay but in a distributed setting, where each node in the network
only knows its neighbors (e.g., its own credit links). Although this
last work is not published yet, I would be glad to share and discuss it
with you if you are interested.

I would be interested on discussing my experiences during my research
regarding not only routing mechanisms on credit networks, but also
privacy preserving payments. I believe that privacy is an interesting
and important aspect that might be worth considering on the ongoing
discussions about ILP.

[1] P. F. Tsuchiya, “The Landmark Hierarchy: A New Hierarchy for Routing
in Very Large Networks,” SIGCOMM Comput. Commun. Rev., vol. 18, no. 4,
pp. 35–42, Aug. 1988.
[2] B. Viswanath, M. Mondal, K. P. Gummadi, A. Mislove, and A. Post,
“Canal: Scaling Social Network-based Sybil Tolerance Schemes,” in
EuroSys ’12, 2012, pp. 309–322.
[3] Moreno-Sanchez, P., Kate, A., Maffei, M., and Pecina, K. Privacy
preserving payments in credit networks: Enabling trust with privacy in
online marketplaces. In NDSS(2015).
Received on Friday, 25 March 2016 21:31:28 UTC

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