1. A system configured to train and use a classifier to classify entities to determine whether the entities are part of a distributed denial of service (DDoS) attack, the system comprising: one or more hardware processors; and one or more computer-readable storage devices having stored thereon instructions that are executable by the one or more hardware processors to configure the system to perform at least the following: train a classifier to use a first classification method to identify probabilities that entities are performing denial of service attacks, the training comprising applying a captured dataset including data flow protocol information associated with known DDoS attacks; using the trained classifier, identify a subset of entities from a set of candidate entities that meet or exceed a threshold probability of performing a denial of service attack; using a second classification method, identify similarity of entities in the identified subset of entities; and based on the similarity, classify individual entities of the subset of entities as belonging to one or more similarity subgroups, each similarity subgroup comprising entities having a probability of participating in a same DDoS.
1. A system configured to train and use a classifier to classify entities to determine whether the entities are part of a distributed denial of service (DDoS) attack, the system comprising: one or more hardware processors; and one or more computer-readable storage devices having stored thereon instructions that are executable by the one or more hardware processors to configure the system to perform at least the following: train a classifier to use a first classification method to identify probabilities that entities are performing denial of service attacks, the training comprising applying a captured dataset including data flow protocol information associated with known DDoS attacks; using the trained classifier, identify a subset of entities from a set of candidate entities that meet or exceed a threshold probability of performing a denial of service attack; using a second classification method, identify similarity of entities in the identified subset of entities; and based on the similarity, classify individual entities of the subset of entities as belonging to one or more similarity subgroups, each similarity subgroup comprising entities having a probability of participating in a same DDoS. 10. The system of claim 1 , wherein using the second classification method, to identify similarity of entities in the subset of entities comprises using hierarchal clustering.