Security analysts are often bogged down by the rate of false positives generated by security information and event management systems. Supervised machine learning, when applied to historical data to predict alert classification, has the potential to transform the security monitoring industry. IBM believes these methods will significantly tighten classification accuracy, decrease false positive rates, boost analyst productivity and improve customer satisfaction. IBM Watson for Security is taking this challenge seriously and investing in predictive and cognitive technologies to build scalable systems for managed security services (MSS)”]