Distributed source coding in the presence of byzantine sensors

Oliver Kosut, Lang Tong

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

The distributed source coding problem is considered when the sensors, or encoders, are under Byzantine attack; that is, an unknown group of sensors have been reprogrammed by a malicious intruder to undermine the reconstruction at the fusion center. Three different forms of the problem are considered. The first is a variable-rate setup, in which the decoder adaptively chooses the rates at which the sensors transmit. An explicit characterization of the variable-rate achievable sum rates is given for any number of sensors and any groups of traitors. The converse is proved constructively by letting the traitors simulate a fake distribution and report the generated values as the true ones. This fake distribution is chosen so that the decoder cannot determine which sensors are traitors while maximizing the required rate to decode every value. Achievability is proved using a scheme in which the decoder receives small packets of information from a sensor until its message can be decoded, before moving on to the next sensor. The sensors use randomization to choose from a set of coding functions, which makes it probabilistically impossible for the traitors to cause the decoder to make an error. Two forms of the fixed-rate problem are considered, one with deterministic coding and one with randomized coding. The achievable rate regions are given for both these problems, and it is shown that lower rates can be achieved with randomized coding.

Original languageEnglish (US)
Pages (from-to)2550-2565
Number of pages16
JournalIEEE Transactions on Information Theory
Volume54
Issue number6
DOIs
StatePublished - Jun 2008
Externally publishedYes

Keywords

  • Byzantine attack
  • Distributed source coding
  • Network security
  • Sensor fusion
  • Slepian-Wolf coding

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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