The latest trends in cybercrime show increasing damage to society and companies' economic assets by cyber attacks, most often conducted with the help of extremely versatile and effective attack tools called malware. Countermeasures taken to limit the impact of this threat often prove to be invalid, or at least can be circumvented through phishing techniques. This is why tireless research is needed to limit the advancement of such significant damage and such malicious techniques. The thesis explores the most widely used techniques for recognizing malicious programs through classification: the ability, from an unknown file, to recognize its characteristics and assign it an identifying label, in order to distinguish malware from safe programs.