Honeywell International Inc.

Smart Information Flow Technologies, LLC

Christopher William Geib

Robert Prescott Goldman

Scott Ehrlich Friedman

Jeffrey Mathew Rye

Steven Alex Harp

David John Musliner

Ryan A VanRiper

Pavan Kantharaju

Richard Gabriel Freedman

Ugur Kuter

A computing machine receives a plurality of observations. The computing machine generates an observation data structure. The computing machine extends, in accordance with the causal structures and hierarchical relationships, the observation data structure to include predicted states or predicted actions that are not from the plurality of observations. The computing machine reduces, in accordance with consistency rules stored in a memory of the computing machine, the extended observation data structure. The computing machine provides an output associated with the reduced observation data structure.

Computer architecture for plan recognition

A computing machine accesses a directed graph representing one or more sequences of actions. The directed graph comprises nodes and edges between the nodes. Each node is either a beginning node, an intermediate node, or an end node. Each intermediate is downstream from at least one beginning node and upstream from at least one end node. Each beginning node in at least a subset of the beginning nodes has an explainability value vector. The computing machine computes, for each first node from among a plurality of first nodes that are intermediate nodes or end nodes, a provenance value representing dependency of an explainability value vector of the first node on the one or more nodes upstream from the first node. The computing machine computes, for each first node, the explainability value vector. The computing machine provides a graphical output representing at least an explainability value vector of an end node.

Machine architecture for computerized plan analysis with provenance

A system and method analyzes queries in a computer network, and identifies problem-causing queries that could be harmful to the system. If a query does not match any queries in a database, the query is transmitted to its destination. If a query matches a query in the database, that query is blocked from transmission to the destination. If a query is transmitted to its destination, and it is later determined that query caused a problem on that destination, that query is added to the database of queries. In one embodiment, a query that does not cause any problems is written to a pool of current up-to-date backup databases that may be used if the main system goes down. In another embodiment, the system tests variants of a query that caused a problem at the destination to attempt to discover other queries that could cause a problem.

System and method for network security

A skeptical system protects an asset by monitoring commands of a user, predicting a plan of the user based on the monitored commands, inferring an actual plan from the predicted plan, receiving information related to an identity of the user, inferring an actual identity of the user from the information, assessing a threat based on the actual plan and the actual user identity, and selecting, from among a plurality of possible responses, a response that is appropriate to the assessed threat.

Skeptical system

A system and method for recognizing a goal of an actor in an environment by considering hypothesized unobserved actions. The method includes providing a plan library that includes a list of possible goals and corresponding plans. Actions of the actor are observed, and the occurrence of hypothesized unobserved actions are considered. Finally, one or more plans consistent with the observed actions and the consideration of hypothesized unobserved actions are identified.

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Minneapolis, MN, United States of America

Christopher William Geib