Abstract: In one approach, a method includes: receiving a reference login event input from a user, the reference login event input being associated with a first session of the user logging into an account; receiving a new login event input from the user, the new login event input being associated with a second session of the user logging into the account; accessing a machine learning model, wherein the machine learning model is trained using data selected based on a similarity of behavior between different users; and authenticating, with the machine learning model, the user for the account, based at least in part on the reference login event input and the new login event input. In examples, the reference and new login event inputs comprise one or more items of biometric data generated by interaction of the user in a web environment and/or a mobile environment for logging into the account.

Abstract: A method for verifying authenticity of a physical document includes receiving an image of a physical document to be authenticated including the physical document and a background. A pre-processed image is produced that includes the physical document separated from the background. The producing includes separating the physical document from the background by semantic segmentation utilizing an artificial neural network trained using an augmented dataset generated by applying geometric transformations over different backgrounds. Features of the pre-processed image are extracted to determine a document type. In response to determining the document type of the physical document, the method includes verifying, utilizing a machine learning classifier, whether the physical document is authentic based on the extracted features relative to expected features for the corresponding document type. An indication of whether the physical document is authentic based on the verifying is generated.