Minimize resources for spam detection: Minimize resources for spam detection - Navruzov, Erkin (MODERN PROBLEMS AND PROSPECTS OF APPLIED MATHEMATICS, 2024)
Annotation. Protection of computer systems from malicious software is considered. As a tool for detecting threats, the solution of the recognition problem with non-overlapping classes by precedents is used. Resource minimization is performed by selection of training sample. During the selection, noise objects are removed and the problem of the minimum coverage of the sample with standards is solved. As additional information about the sample, it is proposed to use indicators of two measures of compactness. The values of these measures reflect the variety of relationships between objects that depend on metrics, linear and nonlinear transformations of features and the scale of their measurements, the dimension of space. First measure is an indicator of the connectivity of class objects, the second is the generalizing ability of recognition algorithms. To determine the generalizing ability of algorithms, it is proposed to use a measure calculated by the number of removed noise objects and minimum coverage standards. The effectiveness of detecting threats from malicious software was demonstrated on a sample of 4595 objects.