Secure Key Generation for Distributed Inference in IoT Invited Presentation

Henri Hentilä, Visa Koivunen, H. Vincent Poor, Rick S. Blum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

A secret key generation scheme is proposed for generating keys to be used for one-time pad encryption. This type of encryption is suitable for e.g., short packet communication in distributed inference in IoT. The scheme exploits the phase of the channel fading coefficient in a Rayleigh fading channel to extract highly correlated key bits at two legitimate parties. Compared to other existing methods, the proposed scheme trades off higher bit error probabilities in the keys for lower error correction communication requirements. The bit error of generated keys is characterized via an approximate upper bound, which is shown to be fairly tight for reasonable signal-to-noise ratios.

Original languageEnglish (US)
Title of host publication2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728111513
DOIs
StatePublished - Apr 16 2019
Event53rd Annual Conference on Information Sciences and Systems, CISS 2019 - Baltimore, United States
Duration: Mar 20 2019Mar 22 2019

Publication series

Name2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019

Conference

Conference53rd Annual Conference on Information Sciences and Systems, CISS 2019
CountryUnited States
CityBaltimore
Period3/20/193/22/19

All Science Journal Classification (ASJC) codes

  • Information Systems

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    Hentilä, H., Koivunen, V., Poor, H. V., & Blum, R. S. (2019). Secure Key Generation for Distributed Inference in IoT Invited Presentation. In 2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019 [8692935] (2019 53rd Annual Conference on Information Sciences and Systems, CISS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CISS.2019.8692935