Search results are received from an initiated free text search of log data from one or more logs, where the free text is performed using search terms entered into a free text search graphical user interface. A set of at least one search result is selected from the search results containing an event desired to be identified in a completed enterprise threat detection (ETD) pattern. A forensic lab application is rendered to complete an ETD pattern. An event filter is added for an event type based on normalized log data to a path. A relative ETD pattern time range is set and an ETD pattern is completed based on the added event filter.

Pattern creation in enterprise threat detection

A computer-implemented method generates a trigger registration for a selected triggering type. The generated trigger registration is stored in a triggering persistency. A received event from an event persistency is analyzed and data associated with the analyzed event is compared with the triggering persistency. Based on the comparison and using a pattern execution framework, an enterprise threat detection (ETD) pattern is processed to perform actions responsive to the received event.

Realtime triggering framework

Subnet information and location information is received from a database by a smart data streaming engine (SDS). A particular subnet of the subnet information is associated with a particular location of the location information by a globally unique location ID value. Log event data received in the SDS is normalized as normalized log event data. The normalized log event data is enriched with subnet and location information as enriched log event data and written into a log event persistence in the database. A subnet ID value retrieved from an enriched log event of the enriched log event data is used by an enterprise threat detection (ETD) system to determine a location associated with the enriched log event using a location ID value associated with the subnet ID.

Location enrichment in enterprise threat detection

A selection of data types is defined from available log data for an evaluation of events associated with an entity. One or more evaluations associated with the entity are defined and reference data is generated from the selection of data types based on the one or more defined evaluations. The one or more evaluations are grouped into a pattern. A three dimensional (3D) score diversity diagram visualization is initialized for display in a graphical user interface, where a point representing the entity in the visualization is localized in 3D space at a coordinate based on two-dimensional (2D) coordinates in a 2D coordinate system of a centroid of the calculated area of a polygon placed to into the 2D coordinate system and defined by the values of each evaluation associated with the entity.

Anomaly detection in enterprise threat detection

A log processing job executing on a log producing computing system is initiated for processing log data associated with the log producing computing system. Log entries are determined to be available for processing. At least one instance of a Log Extractor Factory, Reader, and Transformation component are instantiated for reading and transforming the log data. Read log data is transformed into a common semantic format as transformed log data and transmitted in real-time to a Streaming Component for storage in an Enterprise Threat Detection (ETD) System. A recovery point is stored with a recovery timestamp indicating a next log entry in the log data to process.

Providing semantic connectivity between a java application server and enterprise threat detection system using a J2EE data

A Content Service executing in a cloud-computing-based Cloud Platform receives enterprise threat detection (ETD) Content transmitted from an ETD Content Development System (CDS) as a publication of the ETD Content from the ETD CDS. The received ETD Content is stored into a Content Management System (CMS). A determination is made of a registered Client ETD System for which the ETD Content is relevant. The ETD Content is published to the registered Client ETD System.

Distributing cloud-computing platform content to enterprise threat detection systems

The present disclosure describes methods, systems, and computer program products for performing a frequency domain analysis of activity data for a computer system. One computer-implemented method receiving time domain activity data for a computer system, wherein the time domain activity data comprise activity records associated with the computer system in a time domain; computing, by a hardware processor, frequency domain activity data based on the time domain activity data; and displaying the frequency domain activity data.

Using frequency analysis in enterprise threat detection to detect intrusions in a computer system

A first Event is identified from a normalized log persistency layer, where the first Event is associated with an attack on a computing system. A plurality of Events are fetched from the normalized log persistency layer, where each fetched Event correlates with its neighboring fetched Event by at least one correlation attribute, and each of the fetched Event and the first Event are presented on a graphical user interface as a chain of events. A workspace is generated, where the workspace comprises a series of attack paths, where each attack path corresponds to one Event in the chain of events. An ETD pattern is created based on the attack paths in the workspace.

Pattern creation based on an attack path

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