公开(公告)号：US20250112874A1

公开(公告)日：2025-04-03

申请号：US18374375

申请日：2023-09-28

Applicant: Google LLC

Inventor： Christopher Schneider ,  Bessie S Jiang ,  Martin Sablotny ,  J. Nicolas Watson

IPC: H04L47/80 ,  H04L9/40

Abstract: Baseline data characterizing actions of one or more computing resources associated with one or more entities is received. One or more functional roles performed by the one or more computing resources are identified using a machine learning model, wherein the baseline data is provided as input to the machine learning model. A security-related control to be applied to the one or more computing resources is identified based on the one or more functional roles. The security-related control is applied to the one or more computing resources.

公开(公告)号：US20250013441A1

公开(公告)日：2025-01-09

申请号：US18218302

申请日：2023-07-05

Applicant: Google LLC

Inventor： Christopher Ian Schneider ,  Bessie S. Jiang ,  J. Nicolas Watson

IPC: G06F8/41

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.