Resilient Network Coding in the Presence of Byzantine Adversaries
By Sidharth Jaggi, Michael Langberg, Sachin Rajsekhar Katti, T. Ho, Dina Katabi, Muriel Médard, Michelle Effros. IEEE Transactions on Information Theory, 2008
570 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/8fe6bba46475f527d2a61d32d2ae1e22861ad34f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Dina Katabi
- Sachin Rajsekhar Katti
- Muriel Médard
- Dan Boneh
- Hari Balakrishnan
- Ralf Koetter
- Frank R. Kschischang
- Danilo Silva
In Electrical and Electronic Engineering
- Dina Katabi
- Sachin Rajsekhar Katti
- Muriel Médard
- Dan Boneh
- Ralf Koetter
- Hari Balakrishnan
- Frank R. Kschischang
- Danilo Silva
Citations in the corpus
- A Rank-Metric Approach to Error Control in Random Network Coding (2007, background): “[8] propose a different approach specifically ta rgeted to combat Byzantine adversaries.”
- Resilient Asymptotic Consensus in Robust Networks (2013, background): “The following definitions generalize this notion of redundancy to the entire network.”
- Distributed Function Calculation via Linear Iterative Strategies in the Presence of Malicious Agents (2011, background): “In these cases, the network is assumed to contain a source node that is trying to send information at a certain rate to some destination nodes, and network codes have been developed to maximize this rate i n the presence of malicious attackers [21].”
- Signing a Linear Subspace: Signature Schemes for Network Coding (2009, background): “Information-theoretic methods for enabling recovery from malicious faults work by introducing redundancy into the original packets transmitted by the sender [15] [17] [18].”
- Symbol-level network coding for wireless mesh networks (2008, background): “MIXIT’s network code also builds on recent advances in extending network coding to scenarios with errors and adversaries [7, 12].”