Relative generalized matrix weights of matrix codes for universal security on wire-tap networks

Umberto Martinez Peñas, Rytaro Yamashita Matsumoto

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14 Citations (Scopus)
238 Downloads (Pure)

Abstract

Universal security over a network with linear network coding has been intensively studied. However, previous linear codes and code pairs used for this purpose were linear over a larger field than that used on the network, which restricts the possible packet lengths of optimal universal secure codes, does not allow to apply known list-decodable rank-metric codes and requires performing operations over a large field. In this paper, we introduce new parameters (relative generalized matrix weights and relative dimension/rank support profile) for code pairs that are linear over the field used in the network, and show that they measure the universal security performance of these code pairs. For one code and non-square matrices, generalized matrix weights coincide with the existing Delsarte generalized weights, hence we prove the connection between these latter weights and secure network coding, which was left open. As main applications, the proposed new parameters enable us to: 1) obtain optimal universal secure linear codes on noiseless networks for all possible packet lengths, in particular for packet lengths not considered before, 2) obtain the first universal secure list-decodable rank-metric code pairs with polynomial-sized lists, based on a recent construction by Guruswami et al; and 3) obtain new characterizations of security equivalences of linear codes. Finally, we show that our parameters extend relative generalized Hamming weights and relative dimension/length profile, respectively, and relative generalized rank weights and relative dimension/intersection profile, respectively.

Original languageEnglish
JournalI E E E Transactions on Information Theory
Volume64
Issue number4
Pages (from-to)2529 - 2549
Number of pages21
ISSN0018-9448
DOIs
Publication statusPublished - 2018

Keywords

  • Network coding
  • rank weight
  • relative dimension/rank support profile
  • relative generalized matrix weight
  • universal secure network coding

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