| ARCSIGHT, INC. Patent applications |
| Patent application number | Title | Published |
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| 20110066585 | EXTRACTING INFORMATION FROM UNSTRUCTURED DATA AND MAPPING THE INFORMATION TO A STRUCTURED SCHEMA USING THE NA VE BAYESIAN PROBABILITY MODEL - An “unstructured event parser” analyzes an event that is in unstructured form and generates an event that is in structured form. A mapping phase determines, for a given event token, possible fields of the structured event schema to which the token could be mapped and the probabilities that the token should be mapped to those fields. Particular tokens are then mapped to particular fields of the structured event schema. By using the Naïve Bayesian probability model, a “probabilistic mapper” determines, for a particular token and a particular field, the probability that that token maps to that field. The probabilistic mapper can also be used in a “regular expression creator” that generates a regex that matches an unstructured event and a “parameter file creator” that helps a user create a parameter file for use with a parameterized normalized event generator to generate a normalized event based on an unstructured event. | 03-17-2011 |
| 20100306285 | Specifying a Parser Using a Properties File - A system for generating a parser and using the parser to parse a target file includes a target file description, an output format description, a Parser generator, a Parser, a target file, and a result object. The target file description and the output format description are included in one or more “properties files”, which are text files that include one or more name/value pairs (“properties”). The target file description and the output format description are input into the Parser generator, which outputs the Parser. The target file is input into the Parser, which outputs the result object. The target file description specifies one or more parsers and/or tokenizers that can be used to parse the target file. The parsers and/or tokenizers specified by the target file description are part of the generated Parser. These parsers and/or tokenizers make the Parser more flexible, which enables the Parser to parse semi-structured data. | 12-02-2010 |
| 20100011031 | STORING LOG DATA EFFICIENTLY WHILE SUPPORTING QUERYING - A logging system includes an event receiver and a storage manager. The receiver receives log data, processes it, and outputs a column-based data “chunk.” The manager receives and stores chunks. The receiver includes buffers that store events and a metadata structure that stores metadata about the contents of the buffers. Each buffer is associated with a particular event field and includes values from that field from one or more events. The metadata includes, for each “field of interest,” a minimum value and a maximum value that reflect the range of values of that field over all of the events in the buffers. A chunk is generated for each buffer and includes the metadata structure and a compressed version of the buffer contents. The metadata structure acts as a search index when querying event data. The logging system can be used in conjunction with a security information/event management (SIEM) system. | 01-14-2010 |
| 20090064333 | Pattern Discovery in a Network System - Patterns can be discovered in events collected by a network system. In one embodiment, the present invention includes collecting and storing events from a variety of monitor devices. In one embodiment, a subset of the stored events is provided to a manager as an event stream. In one embodiment, the present invention further includes the manager discovering one or more previously unknown event patterns in the event stream. | 03-05-2009 |
