Abstract: Methods, apparatus, and processor-readable storage media for security-related image processing using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining image data associated with at least one user-provided component; obtaining identifier data associated with the at least one user-provided component; obtaining image data associated with at least one reference component from at least one database using at least a portion of the obtained identifier data; performing a comparison, using at least one pretrained computer vision model, of at least a portion of the obtained image data associated with the at least one user-provided component and at least a portion of the obtained image data associated with the at least one reference component; and performing one or more security-related actions based at least in part on results of the comparison.

Abstract: An apparatus includes at least one processing device configured to obtain information regarding a given asset to be repaired, to generate a recommended troubleshooting action to be performed on the given asset, and to provide the recommended troubleshooting action and the obtained information regarding the given asset as input to an encoder of a machine learning model implementing an attention mechanism. The at least one processing device is also configured to receive, from a decoder of the machine learning model, a predicted success of the recommended troubleshooting action. The at least one processing device is further configured to determine whether the predicted success of the recommended troubleshooting action meets designated criteria, to perform the recommended troubleshooting action responsive to the predicted success meeting the designated criteria, and, to modify the recommended troubleshooting action responsive to the predicted success not meeting the designated criteria.

Abstract: An apparatus includes at least one processing device configured to obtain information regarding a given asset to be repaired, to generate a recommended troubleshooting action to be performed on the given asset, and to provide the recommended troubleshooting action and the obtained information regarding the given asset as input to an encoder of a machine learning model implementing an attention mechanism. The at least one processing device is also configured to receive, from a decoder of the machine learning model, a predicted success of the recommended troubleshooting action. The at least one processing device is further configured to determine whether the predicted success of the recommended troubleshooting action meets designated criteria, to perform the recommended troubleshooting action responsive to the predicted success meeting the designated criteria, and, to modify the recommended troubleshooting action responsive to the predicted success not meeting the designated criteria.