A model for revocation forecasting in public-key infrastructures

Carlos Gañán*, Jorge Mata-Díaz, Jose L Muñoz, Oscar Esparza, Juanjo Alins

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

One of the hardest tasks of a certification infrastructure is to manage revocation. This process consists in collecting and making the revocation status of certificates available to users. Research on this topic has focused on the trade-offs that different revocation mechanisms offer. Much less effort has been conducted to understand and model real-world revocation processes. For this reason, in this paper, we present a novel analysis of real-world collected revocation data and we propose a revocation prediction model. The model uses an autoregressive integrated moving average model. Our prediction model enables certification authorities to forecast the number of revoked certificates in short term.

Original languageEnglish
Pages (from-to)311-331
Number of pages21
JournalKnowledge and Information Systems
Volume43
Issue number2
DOIs
Publication statusPublished - 2015
Externally publishedYes

Keywords

  • ARIMA
  • Certification
  • CRL
  • PKI
  • Revocation

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