Abstract: A method includes generating a modeling language diagram that is indicative of a compiled version of program code. The modeling language diagram includes at least one node corresponding to at least one function in the program code. The method also includes identifying at least one function signature associated with anode state transition between nodes in the modeling language diagram. The method also includes identifying, using a large language model, a particular policy to attribute to the at least one function signature associated with the node state transition. The method further includes performing, using the large language model, a policy compliance operation that ensures a particular portion of the program code complies with the particular policy. The particular portion of the program code is associated with the node state transition. Performing the policy compliance operation includes generating a policy-compliant version of the particular portion of the program code.

Abstract: In various examples, a user may be authenticated without disclosing any confidential or private information of the user. An independent accumulator stores user confidential information, and accumulates items issued by various parties for the user. When another entity requests to verify the item and the user, the accumulator may verify the user by verifying his or her possession of the item and his or her private information. The accumulator may also verify the item with the issuing party and verify that the item was intended for the user. Once verification has occurred, the accumulator informs the requesting entity that their request is confirmed. In this manner, entities may verify items of a user, without requiring the user to disclose any of his or her confidential or private information to the requestor.

Abstract: Apparatuses, systems, and techniques to detect abnormal behavior on clients using one or more neural networks on said clients. In at least one embodiment, use of or behavior on one or more clients is analyzed by a first neural network to detect abnormal behavior compared to a baseline of accepted behavior, and said baseline of accepted behavior is revised over time by a second neural network based on behavior observed on said one or more clients.

Abstract: Apparatuses, systems, and techniques to accelerate training of one or more neural networks. In at least one embodiment, training values for individual nodes in a first neural network are estimated using a second neural network or other estimation technique in order to decrease time required to train the first neural network.

Abstract: A security enhancement technique provides users of an application program with a perceptible cue, such as a visual or audible indication, that a domain and/or link is safe according to a list of safe domains/sites and links. Each identified domain and/or link is compared with domains and/or links defined in a trusted list. The trusted list is maintained by an enterprise system administrator or is provided via an internet browser program. Advantages of this technique are that the user can easily identify domain names that are trusted and does not need to examine each URL path to determine whether or not the domain and/or link is safe. Users may be motivated to scrutinize domains and/or links that are not indicated to be trusted, reducing security breaches.