Risk management process represents the complex problem possessing a number of specific features. Ambiguity of the concept "risk" and variety of manifestations of risk and opportunities of overcoming of its adverse effects are aggravated with that the most part of the parameters participating in process of development of managing decisions have no accurate (numerical) characteristics. Estimates of the majority of concepts are formulated by experts in a verbal form. For overcoming of the specified difficulties in work the method of a numerical assessment of levels of the acceptable is offered and tolerant is risk. The entered metrics allow to start formalization of process of search and acceptance of optimum management decisions for reduction of value of the current risk to the target objective. The offered mathematical model can be the basis for the corresponding software for the purpose of creation of system of decision support in the sphere of a risk management.

Keywords: risk management, acceptable risk, tolerant risk, current risk level, degree of danger of a situation

This article proposes the problem of the anti-virus heuristic analysis. Important feature of static heuristic techniques is dependence of indicators of detection on structure of the training set. Offered the technique of formation a training set . Concepts of a measure of similarity and a matrix of similarity were entered. The measure of similarity shows degree of compliance of one file to another. The matrix of similarity consists of measures of similarity of files of the training set. With use of the entered definitions the technique of formation of the training selection was developed. The main idea of a technique consists what the files which remained in the training set had as it is possible a smaller measure of similarity with the others. The carried-out experimental inspection showed efficiency and the practical importance of the proposed solution.

Keywords: information security, virus protection, heuristic analysis, machine learning, training set, malwares