Kit Dodson (UMIST)
dodson@umist.ac.uk
Designers of secure software systems need to monitor and quantify event clustering in order to minimize information leakage to probes by an attacker, perhaps through introduction of obscuring procedures in a restricted memory device such as a smartcard. An ideal situation would be to have scheduling that to an attacker resembles closely a random sequence of events. The basic `random' model for stochastic events is the Poisson process; for events on a line this results in an exponential distribution of intervals between events.
Here we discuss the elementary differential geometry of manifolds of gamma distributions, which contain exponential distributions as a special case; this gives a means of quantifying departures from randomness and from uniformity.