7. The method of claim 5 , wherein the binary anomaly detection model is represented using a Bloom filter.
5. A method for outputting data based on anomaly detection, comprising: receiving known anomaly signatures; generating, using a hardware processor, n-grams of different sizes using the known anomaly signatures; storing, using the hardware processor, abnormal n-grams in the n-grams of different sizes in a binary anomaly detection model; using 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 outputting, using the hardware processor, the input dataset based on whether the input dataset contains an anomaly.