Abstract: A method and system for performing a neural level vulnerability detection are disclosed. The method includes receiving a neural network model, performing a bit-level corruption check on the received neural network model indicating a potential presence of an embedded malware in the neural network model, and deploying the neural network model. The method further includes scheduling a periodic anomaly detection on the deployed neural network model, performing the periodic anomaly detection on the deployed neural network model for detecting an anomaly at a scheduled time, and when the anomaly is detected on the neural network model, executing an explainable artificial intelligence based embedded malware exploration to identify an alteration made by the embedded malware at a neuron level of the neural network model.

Abstract: In some aspects, the techniques described herein relate to a method including: receiving, at a client computer, a driver script file; creating, by the driver script file, a use-case specific directory; creating, by the driver script file, an application parameters file; retrieving, by the driver script file, a core configuration script file; determining, by the core configuration script file, a required database driver; retrieving, by the core configuration script file, the required database driver; retrieving, by the core configuration script file, a database driver configuration file for the required database driver; populating, by the core configuration script file, the database driver configuration file with a plurality of entries, wherein the plurality of entries in the database driver configuration file comprise entries based on a user input; and validating, by the core configuration script file, a connection defined by the database driver configuration file.

Abstract: In some aspects, the techniques described herein relate to a method including: receiving, at a client computer, a driver script file; creating, by the driver script file, a use-case specific directory; creating, by the driver script file, an application parameters file; retrieving, by the driver script file, a core configuration script file; determining, by the core configuration script file, a required database driver; retrieving, by the core configuration script file, the required database driver; retrieving, by the core configuration script file, a database driver configuration file for the required database driver; populating, by the core configuration script file, the database driver configuration file with a plurality of entries, wherein the plurality of entries in the database driver configuration file comprise entries based on a user input; and validating, by the core configuration script file, a connection defined by the database driver configuration file.

Abstract: Systems and methods for personally identifiable information metadata governance are disclosed. In one embodiment, a method for personally identifiable information (PII) metadata governance may include: (1) receiving, by a PII metadata identification program executed by an electronic device, a data processing flow for a project; (2) retrieving, by the PII metadata identification program, code for the data processing flow from a code repository; (3) identifying, by the PII metadata identification program, potential PII access points in the code; (4) determining, by the PII metadata identification program, that the potential PII access points match PII access points in a PII reference data database; (5) confirming, by the PII metadata identification program, that an individual assigned to the project is entitled access the PII data; and (6) granting, by the PII metadata identification program, access to the PII data to the individual.