公开(公告)号：US11343266B2

公开(公告)日：2022-05-24

申请号：US16436093

申请日：2019-06-10

Applicant: General Electric Company

Inventor： Masoud Abbaszadeh ,  Hema K. Achanta ,  Mustafa Tekin Dokucu ,  Matthew Nielsen ,  Justin Varkey John

IPC: H04L9/40 ,  H04L29/06 ,  H04L41/28 ,  H04L41/16

Abstract: Methods and systems for self-certifying secure operation of a cyber-physical system having a plurality of monitoring nodes. In an embodiment, an artificial intelligence (AI) watchdog computer platform obtains, using the output of a local features extraction process of time series data of a plurality of monitoring nodes of a cyber-physical system and a global features extraction process, global features extraction data. The AI watchdog computer platform then obtains reduced dimensional data, generates an updated decision boundary, compares the updated decision boundary to a certification manifold, determines based on the comparison that the updated decision boundary is certified, and determines, based on an anomaly detection process, whether the cyber-physical system is behaving normally or abnormally.

公开(公告)号：US11005870B2

公开(公告)日：2021-05-11

申请号：US16201461

申请日：2018-11-27

Applicant: General Electric Company

Inventor： Weizhong Yan ,  Masoud Abbaszadeh ,  Matthew Nielsen ,  Justin Varkey John

IPC: H04L29/06

Abstract: Systems and methods may be associated with a cyber-physical system, and a blueprint repository data store may contain electronic files that represent behavior-based asset monitoring parameters for different cyber-physical system asset types. A behavior-based asset monitoring creation computer platform may receive an indication of an asset type of the cyber-physical system. The behavior-based asset monitoring creation computer platform may then search the blueprint repository data store and retrieve an electronic file representing behavior-based asset monitoring parameters for the asset type of the cyber-physical system to be monitored. The behavior-based asset monitoring creation computer platform may also receive, from the remote operator device, adjustments to the retrieved behavior-based asset monitoring parameters and automatically configure, based on the adjusted behavior-based asset monitoring parameters, at least a portion of settings for an abnormal detection model. The abnormal detection model may then be created about output to be executed by an abnormal detection platform.