Investigation of a Markov model for computer system security threats

In this work, a model for computer system security threats formulated in terms of Markov processes is investigated. In the framework of this model the functioning of the computer system is considered as a sequence of failures and recovery actions which appear as results of information security threats acting on the system. We provide a detailed description of the model: the explicit analytical formulas for the probabilities of computer system states at any arbitrary moment of time are derived, some limiting cases are discussed, and the long-run dynamics of the system is analysed. The dependence of the security state probability (i.e. the state for which threats are absent) on the probabilities of threats is separately investigated. In particular, it is shown that this dependence is qualitatively different for odd and even moments of time. For instance, in the case of one threat the security state probability demonstrates non-monotonic dependence on the probability of threat at even moments of time; this function admits at least one local minimum in its domain of definition. It is believed that the mentioned feature is important because it allows to locate the most dangerous areas of threats where the security state probability can be lower then the permissible level. Finally, we introduce an important characteristic of the model, called the relaxation time, by means of which we construct the permitting domain of the security parameters. Also the prospects of the received results application to the problem of finding the optimal values of the security parameters is discussed.