Real-time detection and classification of anomalous events in streaming data
Patent
·
OSTI ID:1247988
A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. The system can include a plurality of anomaly detectors that together implement an algorithm to identify low probability events and detect atypical traffic patterns. The atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-00OR22725
- Assignee:
- UT-Battelle, LLC (Oak Ridge, TN)
- Patent Number(s):
- 9,319,421
- Application Number:
- 14/053,248
- OSTI ID:
- 1247988
- Resource Relation:
- Patent File Date: 2013 Oct 14
- Country of Publication:
- United States
- Language:
- English
Similar Records
Detection of anomalous events
Compression Analytics for Classification and Anomaly Detection within Network Communication
ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network
Patent
·
Tue Jun 07 00:00:00 EDT 2016
·
OSTI ID:1247988
Compression Analytics for Classification and Anomaly Detection within Network Communication
Journal Article
·
Fri Oct 26 00:00:00 EDT 2018
· IEEE Transactions on Information Forensics and Security
·
OSTI ID:1247988
+1 more
ThunderSecure: deploying real-time intrusion detection for 100G research networks by leveraging stream-based features and one-class classification network
Journal Article
·
Wed Mar 16 00:00:00 EDT 2022
· International journal of information security
·
OSTI ID:1247988