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 language | English |
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Pages (from-to) | 311-331 |
Number of pages | 21 |
Journal | Knowledge and Information Systems |
Volume | 43 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2015 |
Externally published | Yes |
Keywords
- ARIMA
- Certification
- CRL
- PKI
- Revocation