Anomaly detection involves the technique of identifying abnormal deviations in system behavior from established patterns. Any event that deviates significantly from the ordinary norm is flagged as an anomaly by anomaly detection systems. By way of illustration, if the average value of a given feature is 100 and its standard deviation is 10, then a value of 200 should raise red flags in an anomaly detection system.
Anomaly Detection in Al & Its Applications
Anomaly detection has several practical uses in AI, including bolstering system stability and protection. Some of the many ways anomaly detection is used in the field of artificial intelligence are as follows:
1. Cybersecurity
One usage of anomaly detection is in cybersecurity, where it can be used for data such as network traffic, user behavior, and system logs. Anomalies can be used to detect harmful behavior like cyber-attacks or system breaches since they reveal deviations from the norm.
2. Predictive Maintenance
Machine and equipment sensor data (such as temperature, vibration, and pressure) can be monitored and analyzed for anomalies as part of Predictive Maintenance. Identifying out-of-the-ordinary behavior allows for anticipating equipment failures to organize repairs in advance.
3. Fraud Detection
Anomaly detection may be employed to spot suspicious activity in financial transaction data like credit card purchases. Anomalies are a useful indicator of potentially fraudulent activities like unlawful activities or money laundering because of the patterns they reveal.
4. Medical Diagnosis
Anomaly detection has diagnostic applications in the medical field, including identifying outliers in medical data like electrocardiogram (ECG) signals, magnetic resonance imaging (MRI), and genomic information. Potential health hazards can be detected, and preventative measures can be taken if abnormalities are identified.
5. Manufacturing Quality Control
Anomaly detection may be utilized in manufacturing quality control to look for outliers in product quality data, including dimensions, weights, and colors. Potential flaws in the product can be found and fixed before it goes out the door if anomalies are detected.
In conclusion, anomaly detection is an effective method that sees widespread use in the artificial intelligence sector.
