Abstract: Presented herein are systems and methods of evaluating network operations associated with computing systems. A server may receive, from a computing system, an electronic request to execute a first network operation using a plurality of attributes provided by an end user device to the computing system. The first network operation may be initiated via the end user device. The server may retrieve (i) a digital fingerprint associated with an identity of the computing system and (ii) a plurality of network operation metrics associated with the computing system. The server may execute, using the digital fingerprint and the plurality of network operation metrics, a machine learning (ML) model to generate a likelihood of fraud caused by the computing system. The server may, in response to the likelihood of fraud satisfying a threshold, execute a second network operation using the plurality of attributes, instead of executing the first network operation.

Abstract: Presented herein are systems and methods of training machine learning (ML) models to determine likelihoods of fraud in network operations caused by computing systems. A server may generate training data to include (i) a digital fingerprint associated with an identity of a computing system of a plurality of computing systems and (ii) a plurality of network operation metrics associated with the computing system. The server may label the training data to indicate whether fraudulence is caused by the computing system. The server may execute, using the training data, a ML model having a plurality of weights to generate a likelihood of fraud caused by the computing system. The server may compare the likelihood of fraud with labeled training data to determine an error metric in accordance with a loss function. The server may update at least one of the plurality of weights using the error metric.

Abstract: Presented herein are systems and methods of evaluating network operations associated with computing systems. A server may receive, from a computing system, an electronic request to execute a first network operation using a plurality of attributes provided by an end user device to the computing system. The first network operation may be initiated via the end user device. The server may retrieve (i) a digital fingerprint associated with an identity of the computing system and (ii) a plurality of network operation metrics associated with the computing system. The server may execute, using the digital fingerprint and the plurality of network operation metrics, a machine learning (ML) model to generate a likelihood of fraud caused by the computing system. The server may, in response to the likelihood of fraud satisfying a threshold, execute a second network operation using the plurality of attributes, instead of executing the first network operation.