Invention Grant
- Patent Title: Detection of an adversarial backdoor attack on a trained model at inference time
-
Application No.: US16451110Application Date: 2019-06-25
-
Publication No.: US11601468B2Publication Date: 2023-03-07
- Inventor: Nathalie Baracaldo Angel , Yi Zhou , Bryant Chen , Ali Anwar , Heiko H. Ludwig
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Amin, Turocy & Watson, LLP
- Main IPC: H04L9/40
- IPC: H04L9/40 ; G06N5/04 ; G06N20/00

Abstract:
Systems, computer-implemented methods, and computer program products that can facilitate detection of an adversarial backdoor attack on a trained model at inference time are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a log component that records predictions and corresponding activation values generated by a trained model based on inference requests. The computer executable components can further comprise an analysis component that employs a model at an inference time to detect a backdoor trigger request based on the predictions and the corresponding activation values. In some embodiments, the log component records the predictions and the corresponding activation values from one or more layers of the trained model.
Information query