Log in
Enquire now
‌

US Patent 11055405 Anomaly event detection using frequent patterns

Patent 11055405 was granted and assigned to Splunk on July, 2021 by the United States Patent and Trademark Office.

OverviewStructured DataIssuesContributors

Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Splunk
Splunk
Current Assignee
Splunk
Splunk
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11055405
Date of Patent
July 6, 2021
Patent Application Number
16399734
Date Filed
April 30, 2019
Patent Citations
‌
US Patent 10904277 Threat intelligence system measuring network threat levels
‌
US Patent 10756983 Intent-based analytics
Patent Citations Received
‌
US Patent 12095639 Method, device and system for improving performance of point anomaly based data pattern change detection associated with network entity features in a cloud-based application acceleration as a service environment
0
‌
US Patent 11520792 Distributed cardinality optimization
‌
US Patent 11558408 Anomaly detection based on evaluation of user behavior using multi-context machine learning
‌
US Patent 11586729 Frequent pattern based anomaly event detection
‌
US Patent 12026253 Determination of likely related security incidents
0
‌
US Patent 12088473 Method, device and system for enhancing predictive classification of anomalous events in a cloud-based application acceleration as a service environment
0
‌
US Patent 11516069 Aggregate notable events in an information technology and security operations application
‌
US Patent 11323304 Self-learning correlation of network patterns for agile network operations
...
Patent Primary Examiner
‌
Christopher A Revak
Patent abstract

A method is disclosed. The method includes: receiving, at a computing device, an event log including a plurality of events, where the plurality of events are derived from machine data generated by components of an information technology environment; determining a first score associated with a first granularity level by comparing a first event from the event log with a first plurality of frequent patterns generated for the first granularity level; determining a second score associated with a second granularity level by comparing the first event with a second plurality of frequent patterns generated for the second granularity level; determining an aggregate score for the first event based on the first score and the second score; comparing the aggregate score for the first event with an anomaly score threshold; and issuing an alert identifying the first event as an anomaly based on the aggregate score exceeding the anomaly score threshold.

Timeline

No Timeline data yet.

Further Resources

Title
Author
Link
Type
Date
No Further Resources data yet.

References

Find more entities like US Patent 11055405 Anomaly event detection using frequent patterns

Use the Golden Query Tool to find similar entities by any field in the Knowledge Graph, including industry, location, and more.
Open Query Tool
Access by API
Golden Query Tool
Golden logo

Company

  • Home
  • Press & Media
  • Blog
  • Careers
  • WE'RE HIRING

Products

  • Knowledge Graph
  • Query Tool
  • Data Requests
  • Knowledge Storage
  • API
  • Pricing
  • Enterprise
  • ChatGPT Plugin

Legal

  • Terms of Service
  • Enterprise Terms of Service
  • Privacy Policy

Help

  • Help center
  • API Documentation
  • Contact Us