View source for 18157278. SYSTEM AND METHOD FOR DETECTION OF TRANSIENT DATA DRIFT WHILE PERFORMING ANOMALY DETECTION simplified abstract (Dell Products L.P.)

=SYSTEM AND METHOD FOR DETECTION OF TRANSIENT DATA DRIFT WHILE PERFORMING ANOMALY DETECTION=


==Organization Name==

[[:Category:Dell Products L.P.|Dell Products L.P.]]


[[Category:Dell Products L.P.]]

==Inventor(s)==

[[:Category:OFIR Ezrielev of Be'er Sheva (IL)|OFIR Ezrielev of Be'er Sheva (IL)]][[Category:OFIR Ezrielev of Be'er Sheva (IL)]]

==SYSTEM AND METHOD FOR DETECTION OF TRANSIENT DATA DRIFT WHILE PERFORMING ANOMALY DETECTION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18157278 titled 'SYSTEM AND METHOD FOR DETECTION OF TRANSIENT DATA DRIFT WHILE PERFORMING ANOMALY DETECTION

'''Simplified Explanation:'''
The patent application discusses methods and systems for identifying transient data drift during anomaly detection in a distributed environment.

* An anomaly detector and data collectors work together to identify data drift.
* The detector uses inference models to detect data drift and determine if it is transient.
* If transient data drift is detected, the inference models are adjusted accordingly.

'''Key Features and Innovation:'''
* Utilizes an anomaly detector and data collectors to identify transient data drift.
* Uses pairs of inference models to detect and analyze data drift.
* Automatically adjusts inference models based on the detection of transient data drift.

'''Potential Applications:'''
* Anomaly detection in distributed systems.
* Monitoring and maintaining data integrity in real-time.
* Enhancing the accuracy of anomaly detection algorithms.

'''Problems Solved:'''
* Identifying and addressing transient data drift during anomaly detection.
* Ensuring the reliability and accuracy of anomaly detection systems in dynamic environments.

'''Benefits:'''
* Improved accuracy in detecting anomalies.
* Real-time monitoring of data drift.
* Enhanced performance of anomaly detection algorithms.

'''Commercial Applications:'''
The technology can be applied in various industries such as cybersecurity, finance, healthcare, and manufacturing to enhance anomaly detection systems and ensure data integrity.

'''Questions about Transient Data Drift:'''
1. What are the key components of the system used to identify transient data drift?
2. How does the system differentiate between transient data drift and permanent data drift?


==Original Abstract Submitted==

Methods and systems for identifying transient data drift while performing anomaly detection in a distributed environment are disclosed. To identify transient data drift, a system may include an anomaly detector and one or more data collectors. The anomaly detector may identify a first data drift using a first pair of inference models. The anomaly detector may obtain additional data from the one or more data collectors and determine whether a second data drift has occurred using a second pair of inference models. If a second data drift has occurred, the anomaly detector may utilize the first pair of inference models to determine whether the first data drift was a transient data drift. If the first data drift was a transient data drift, the second pair of inference models may be replaced with the first pair of inference models.



[[Category:G06N5/04]]
[[Category:CPC_G06N5/04]]