Hamiltonian structure for a differential system from a modified Laguerre weight via the geometry of the modified third Painlevé equation

Recurrence coefficients of semi-classical orthogonal polynomials are often related to the solutions of special nonlinear second-order differential equations known as the Painlevé equations. Each Painlevé equation can be written in a standard form as a non-autonomous Hamiltonian system, so it is natural to ask whether differential systems satisfied by the recurrence coefficients also possess Hamiltonian structures. We consider recurrence coefficients for a modified Laguerre weight which satisfy a differential system known to be related to the modified third Painlevé equation and identify a Hamiltonian structure for it by constructing its space of initial conditions. We also discuss a transformation from this system to the modified third Painlevé equation which simultaneously identifies a discrete system for the recurrence coefficients with a discrete Painlevé equation

MEASURING INCONSISTENCY IN A NETWORK INTRUSION DETECTION RULE SET BASED ON SNORT

In this preliminary study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which are based on Snort and incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. We measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. Finally, we propose a new measure of inconsistency for prioritized knowledge which incorporates the normalized number of atoms in a language involved in inconsistency to provide a deeper inspection of inconsistent formulae. We conclude that such measures are useful for the network intrusion domain assuming that introducing expert knowledge for correlation of rules is feasible.<br/