17938758. SYSTEM AND METHOD FOR MEMORY-LESS ANOMALY DETECTION simplified abstract (Dell Products L.P.)
Contents
- 1 SYSTEM AND METHOD FOR MEMORY-LESS ANOMALY DETECTION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEM AND METHOD FOR MEMORY-LESS ANOMALY DETECTION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SYSTEM AND METHOD FOR MEMORY-LESS ANOMALY DETECTION
Organization Name
Inventor(s)
OFIR Ezrielev of Beer Sheva (IL)
NADAV Azaria of Beer Sheva (IL)
SYSTEM AND METHOD FOR MEMORY-LESS ANOMALY DETECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 17938758 titled 'SYSTEM AND METHOD FOR MEMORY-LESS ANOMALY DETECTION
Simplified Explanation
The abstract of the patent application describes methods and systems for anomaly detection in a distributed environment. An anomaly detector and data collectors work together to detect anomalies in data and re-train the inference model as needed. After detection and re-training, the data is discarded to remove it from the anomaly detector.
- Anomaly detection in a distributed environment
- System includes an anomaly detector and data collectors
- Anomaly detector uses an inference model to detect anomalies in data
- Inference model may require periodic re-training
- Data collected from data collectors is used to re-train the inference model
- Data is discarded after anomaly detection and re-training
Potential Applications
The technology can be applied in various industries such as cybersecurity, network monitoring, fraud detection, and predictive maintenance.
Problems Solved
1. Efficient anomaly detection in a distributed environment 2. Continuous improvement of the inference model through re-training
Benefits
1. Early detection of anomalies 2. Improved accuracy in anomaly detection 3. Reduced false positives
Potential Commercial Applications
Optimizing anomaly detection systems for cybersecurity companies SEO Optimized Title: "Commercial Applications of Anomaly Detection in Distributed Environments"
Possible Prior Art
One possible prior art could be traditional anomaly detection systems that do not involve re-training the inference model based on data collected from data collectors.
What is the impact of this technology on cybersecurity measures?
This technology can significantly enhance cybersecurity measures by enabling early detection of anomalies in a distributed environment, thereby preventing potential security breaches.
How does this innovation improve upon existing anomaly detection systems?
This innovation improves upon existing anomaly detection systems by incorporating re-training of the inference model based on data collected from data collectors, leading to more accurate and efficient anomaly detection.
Original Abstract Submitted
Methods and systems for anomaly detection in a distributed environment are disclosed. To manage anomaly detection, a system may include an anomaly detector and one or more data collectors. The anomaly detector may detect anomalies in data obtained from one or more of the data collectors using an inference model. To perform anomaly detection, the inference model may require periodic re-training. Data collected from the one or more data collectors may be used to re-train the inference model as needed. Following anomaly detection and/or inference model re-training, the data may be discarded to remove the data from the anomaly detector.
