1. A computerized method for detecting premium attacks by an attack classification system including one or more hardware processors and storage medium, the method comprising: receiving, by the attack classification system, analytic information; generating, by the attack classification system, logical representations for different portions of the analytic information represented as a nodal graph, the logical representations include objects, properties, and relationships between the objects and the properties; filtering, by the attack classification system, a first set of one or more relationships from the relationships, each of the first set of relationships provides lesser assistance in clustering the objects and the properties than a remaining plurality of relationships from the relationships; performing, by the attack classification system, a clustering operation that forms one or more clusters by removing a second set of one or more relationships from the remaining plurality of relationships, the one or more clusters includes a first cluster being a logical representation of a first plurality of objects of the objects, a first plurality of properties of the properties and a plurality of relationships being the remaining plurality of relationships excluding the second set of relationships; analyzing, by the attack classification system, at least the first cluster of the one or more clusters to determine features of at least the first cluster; introducing the determined features associated with the first cluster into the nodal graph; and analyzing the features of the first cluster to determine whether the first plurality of objects, the first plurality of properties and the plurality of relationships forming the first cluster are associated with a premium attack, the analyzing of the features of the first cluster comprises applying rule-based constraints to the features of at least the first cluster to determine that the features correspond to cluster features that are commonly present in premium attacks.