Multishot Adversarial Network Decoding
Giuseppe Cotardo,Gretchen L. Matthews,Alberto Ravagnani +2 more
- 17 Jul 2023
TL;DR: In this paper , the authors investigate adversarial network coding and decoding focusing on the multishot regime, where errors can occur on a proper subset of the network edges and are modeled via an adversarial channel.
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Abstract: We investigate adversarial network coding and decoding focusing on the multishot regime. Errors can occur on a proper subset of the network edges and are modeled via an adversarial channel. The paper contains both bounds and capacity-achieving schemes for the Diamond Network and the Mirrored Diamond Network. We also initiate the study of the generalizations of these networks.
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References
Coding for Errors and Erasures in Random Network Coding
Ralf Koetter,Frank R. Kschischang +1 more
- 24 Jun 2007
TL;DR: In this article, the problem of error control in a non-coherent random network coding channel is considered, where the problem is modelled as the injection into the network of a basis for a vector space V and the collection by the receiver of a base vector space U, under which a minimum distance decoder achieves correct decoding if the dimension of the space V U is large enough.
Resilient Network Coding in the Presence of Byzantine Adversaries
Sidharth Jaggi,Michael Langberg,Sachin Katti,Tracey Ho,Dina Katabi,Muriel Medard,Michelle Effros +6 more
TL;DR: This paper introduces the first distributed polynomial-time rate-optimal network codes that work in the presence of Byzantine nodes, and presents algorithms that target adversaries with different attacking capabilities.
Multishot Codes for Network Coding: Bounds and a Multilevel Construction
TL;DR: This paper explores the idea of using the subspace channel more than once and investigates the so called multishot subspace codes, and presents definitions for the problem, a motivating example, lower and upper bounds for the size of Codes, and a multilevel construction of codes based on block-coded modulation.
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Adversarial Models and Resilient Schemes for Network Coding
Leah Nutman,Michael Langberg +1 more
TL;DR: Three adversarial models of a distributed polynomial-time rate-optimal network-coding scheme that works in the presence of Byzantine faults are revisited and augmented with three, arguably realistic, models.
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Adversarial Network Coding
TL;DR: A combinatorial framework for adversarial network coding is presented, and upper bounds on three notions of capacity—the one-shot capacity, the zero-error capacity, and the compound zero- error capacity—are obtained for point-to-point channels, and generalized to corresponding capacity regions appropriate for multi-source networks.
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