20240054211. DETECTING ANOMALOUS DATA simplified abstract (International Business Machines Corporation)
DETECTING ANOMALOUS DATA
Organization Name
International Business Machines Corporation
Inventor(s)
DETECTING ANOMALOUS DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240054211 titled 'DETECTING ANOMALOUS DATA
Simplified Explanation
The patent application describes a method for detecting anomalous data by using multiple models on a dataset and evaluating the results to determine a combined score threshold for defining anomalies.
- Detecting anomalous data by applying multiple models to a dataset
- Evaluating the detection results for each model
- Determining a combined score for the detection results
- Setting a combined score threshold for defining anomalies
- Defining a set of detected anomalies based on the combined score and threshold
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- Potential Applications
- Fraud detection in financial transactions
- Intrusion detection in cybersecurity
- Quality control in manufacturing processes
- Problems Solved
- Identifying anomalies in large datasets
- Improving accuracy in anomaly detection
- Streamlining the detection process by using multiple models
- Benefits
- Enhanced detection of anomalous data
- Increased efficiency in identifying anomalies
- Improved overall data security and quality control
Original Abstract Submitted
detecting anomalous data by applying a plurality of models to a data set to yield detection results including anomalous data, applying evaluation methods to the detection results for each of the plurality of models, determining a combined score for the detection results according to the evaluation methods, determining a combined score threshold, and defining a set of detected anomalies according to the combined score and the combined score threshold.
