Within the telecommunication services provided by different companies in the sector, they make use of the electromagnetic spectrum, for which they must use licensed electromagnetic spectrum bands and generally each country, through auctions, allows these companies to use frequency spaces to provide a service, however, the optimization of the spectrum plays a very important role, especially when it is identified that there are spaces that are being used illegally and affect service performance[1]. However, optimizing the spectrum plays a very important role and even more so when it is identified that there are spaces that are being used illegally and affect the operation of the service[1]. In order to identify these attacks, an SVM (support vector machine) was implemented, which makes use of an optimal separation hyperplane where the data is grouped into two groups, the first one representing The first group represents data that are part of a malicious attack and the other group represents data that are not an attack. group those that are not an attack, so defining a maximum margin will allow us to identify whether the data sample captured is a malicious attack or not. The first group represents data that is part of a malicious attack and the other group represents data that is not an attack. It is worth mentioning It is worth mentioning that the dataset created with the energy levels that are taken and with the use of the and with the use of entropy, which helps us to identify the amount of average information contained in the measurements taken. information contained in the measurements taken.