Abstract: Described herein are systems and methods for fraud detection in network operations. The method may receive a request for execution of a network operation, the request including a first identifier associated with a user device. The method may extract, using the first identifier, attributes of the network operation and user device attributes. The method may extract a second identifier previously generated for the user device. The method may execute a cryptographic protocol using the second identifier and a cryptographic key to generate a first authentication code. The method may execute a machine learning model to predict a likelihood of fraud using mismatched attributes based on determining that the first authentication code matches a second authentication code parsed from the first identifier. The method may reject the request to execute the network operation in response to determining that a prediction of likelihood of fraud fails to satisfy a security threshold.

Abstract: A method and apparatus for using cryptographically signed secure identifiers to detect fraud during network based transactions are described. The method may include receiving a transaction from a user device, the transaction comprising a secure identifier purported to be associated with the user device, and the transaction further comprising transaction data. The method may also include extracting a first identifier and a second identifier from the secure identifier purported to be associated with the user device, and then regenerating a true second identifier using the first identifier. Furthermore, when it is determined that the true second identifier matches the second identifier extracted from the secure identifier purported to be associated with the user device, the method may include determining that the secure identifier is valid, and processing the transaction based at least in part on the determination that the secure identifier is valid.