- 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>
Hello, 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). http://www.internetsociety.org/doc/privacy-preserving-payments-credit-networks-enabling-trust-privacy-online-marketplaces
Received on Friday, 25 March 2016 21:31:28 UTC