International Business Machines Corporation

Ritesh Kumar

Srinivas Babu Tummalapenta

M Krishnakant Achary

Rashmiranjan Pradhan

According to one embodiment, a method, computer system, and computer program product for anomaly detection is provided. The embodiment may include receiving login event data of a customer. The embodiment may include labeling each login request of the event data as non-anomalous or anomalous. The embodiment may include performing aggregate feature extraction for each login request. The embodiment may include filtering data of anomalous login requests from data of non-anomalous login requests. The embodiment may include training an autoencoder machine learning model using the data of non-anomalous login requests to learn non-anomalous login request behavior. The embodiment may include passing the data of anomalous login requests through the trained autoencoder ML model to obtain enriched data. The embodiment may include training a classifier model using the enriched data to identify anomalous login requests and output a classification with confidence value.

Growing community of inventors

Pune, India

Ritesh Kumar