Detection of Clustering in Graphs in Network Security Analysis

摘要

A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user/entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies/threats were previously known. The security platform can include both real-time and batch paths/modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

主权项

1. A method comprising:
receiving, at a computer system, event data indicative of network activity of a plurality of entities; constructing, by the computer system and based on the event data, a graph that represents relationships among the plurality of entities, the graph including a plurality of nodes that each represent a different one of the entities and a plurality of edges that represent relationships between pairs of the nodes; performing, by the computer system, a cluster identification process to identify a node cluster of the plurality nodes, the cluster identification process including computing L1-norm values for the nodes to assign positions to the nodes on a one-dimensional (1D) grid, based on the graph, and identifying the node cluster based on the assigned positions of the nodes on the 1D grid; and detecting, by the computer system, a network security anomaly based on the identified node cluster.