Unifying notions of generalized weights for universal security on wire-tap networks

TL;DR

This paper introduces new parameters for linear codes over the same field as the network to optimize universal security in wire-tap networks, extending previous concepts and enabling better code design.

Contribution

It proposes relative dimension/rank support profile and relative generalized matrix weights, unifying and extending existing security parameters for linear codes in network coding.

Findings

New parameters measure universal security performance.

Properties include monotonicity, bounds, and duality.

Parameters extend and improve upon existing weights.

Abstract

Universal security over a network with linear network coding has been intensively studied. However, previous linear codes used for this purpose were linear over a larger field than that used on the network. In this work, we introduce new parameters (relative dimension/rank support profile and relative generalized matrix weights) for linear codes that are linear over the field used in the network, measuring the universal security performance of these codes. The proposed new parameters enable us to use optimally universal secure linear codes on noiseless networks for all possible parameters, as opposed to previous works, and also enable us to add universal security to the recently proposed list-decodable rank-metric codes by Guruswami et al. We give several properties of the new parameters: monotonicity, Singleton-type lower and upper bounds, a duality theorem, and definitions and characterizations of equivalences of linear codes. Finally, we show that our parameters strictly extend relative dimension/length profile and relative generalized Hamming weights, respectively, and relative dimension/intersection profile and relative generalized rank weights, respectively. Moreover, we show that generalized matrix weights are larger than Delsarte generalized weights.