A Modeling of Certificate Revocation and Its Application to Synthesis of Revocation Traces

One of the hardest tasks of a public key infrastructure (PKI) is to manage revocation. New communication paradigms push the revocation system to the limit and an accurate resource assessment is necessary before implementing a particular revocation distribution system. In this context, a precise modeling of certificate revocation is necessary. In this paper, we analyze empirical data from real certification authorities (CAs) to develop an accurate and rigorous model for certificate revocation. One of the key findings of our analysis is that the certificate revocation process is statistically self-similar. The proposed model is based on an autoregressive fractionally integrated moving average (ARFIMA) process. Then, using this model, we show how to build a synthetic revocation generator that can be used in simulations for resource assessment. Finally, we also show that our model produces synthetic revocation traces that are indistinguishable for practical purposes from those corresponding to actual revocations.