Pattern recognition systems have been increasingly used in security applications, although it is known that carefully crafted attacks can compromise their security. We advocate that simulating a proactive arms race is crucial to identify the most relevant vulnerabilities of pattern recognition systems, and to develop countermeasures in advance, thus improving system security. We summarize a framework we recently proposed for designing proactive secure pattern recognition systems and review its application to assess the security of biometric recognition systems against poisoning attacks.