47. A system for outputting data based on anomaly detection, comprising: a digital processing device that: receives known anomaly signatures; generates n-grams of different sizes using the known anomaly signatures; stores abnormal n-grams in the n-grams of different sizes in a binary anomaly detection model; uses the binary anomaly detection model to determine whether an input dataset contains an anomaly, wherein the binary anomaly detection model is used to determine whether the input dataset contains an anomaly by checking the binary anomaly detection model for an n-gram in the input dataset; and outputs the input dataset based on whether the input dataset contains an anomaly.
47. A system for outputting data based on anomaly detection, comprising: a digital processing device that: receives known anomaly signatures; generates n-grams of different sizes using the known anomaly signatures; stores abnormal n-grams in the n-grams of different sizes in a binary anomaly detection model; uses the binary anomaly detection model to determine whether an input dataset contains an anomaly, wherein the binary anomaly detection model is used to determine whether the input dataset contains an anomaly by checking the binary anomaly detection model for an n-gram in the input dataset; and outputs the input dataset based on whether the input dataset contains an anomaly. 49. The system of claim 47 , wherein the binary anomaly detection model is represented using a Bloom filter.