Abstract: A computer-implemented method includes: obtaining, by a computing device, location information of a user attempting to gain access to a system; generating, by the computing device, a plurality of images from the location information, the plurality of images including at least one image representative of the location of the user; presenting, by the computing device, the plurality of images to the user; validating, by the computing device, the user by determining that the user has selected the at least one image representative of the location information of the user; and allowing, by the computer device, the user to access the system based on the user being validated.

Abstract: Embodiments relate to performing user validation using local resources in order to permit or deny access to computer resources. An aspect includes in response to receiving a request for access, selecting a selected resource type from a plurality of resource types and selecting a selected user resource from a user resource pool, the selected user resource having the selected resource type. An aspect includes executing a machine learning model to output a prompt in response to inputting the selected user resource, executing a generative artificial intelligence (AI) engine to output generated resources in response to inputting the prompt, and performing an authentication by presenting the generated resources and the selected user resource.

Abstract: Embodiments build an inventory of existing backups in a legacy system, initiate a restore for the existing backups in the legacy system, intercept a plurality of operations of the legacy system, send data which comprises a specific marker pattern in response to intercepting the plurality of operations, and build a storage map using the data which comprises the specific marker pattern.

Abstract: Computer-implemented methods for a challenge-response authentication system using generative artificial intelligence (AI). Aspects include generating a prompt for an object of a randomly selected output type. Aspects further include generating a solution object of the randomly selected output type based on the prompt using a generative AI engine. Aspects also include generating a candidate object of the randomly selected output type based on a modified prompt using the generative AI engine. Aspects further include presenting a challenge-response test comprising a question based on the prompt, the solution object, and the candidate object to a user device. Aspects also include performing a responsive action in response to receiving a response to the challenge-response test from the user device comprising an object selection.