Raytheon Company

Nightwing Group, Llc.

Torsten Staab

Jody Dale Verret

Richard W Ely

Stephen J Raif

Susan N Gottschlich

Nathan T Palmer

Steven B Seida

Michael M Furusawa

David James Theodore

Daniel Rose

Travis Durbin

A method, comprising: detecting a first cyber event; instantiating a report, the report including an identifier corresponding to the first cyber event; generating a signature for a system log and classifying the signature for the system log with a first neural network; and adding the system log to the report based on an outcome of the classification of the signature for the system log, wherein the system log is added to the report only when the signature for the system log is classified into a predetermined category.

Adaptive data selection and reporting

Embodiments regard secure virtual encryptor provisioning. A method can include deriving, by a key management system (KMS), virtual encryptor (VE) token data that associates a VE with a user token, signing, by the KMS, a VE executable file, verifying the signature, by a system root of trust (RoT) of a virtual encryptor system (VES), the VE, responsive to verifying signature, loading, by the VES, the executable file on a virtual machine (VM), receiving the user token data from the user device, and executing the VE responsive to determining an operation on a combination of the user token and the token data associated with the VE returns a specified value.

High assurance virtual encryptor system

Evasive resiliency countermeasures techniques that include: implementing a cyber asset in a network element of a plurality of network elements, monitoring operations of the network; detecting an adverse event within the network; in response to detecting the adverse event, removing an availability of the cyber asset at the network element; determining when the adverse event has ended; and, in response to determining that the adverse event has ended, restoring the availability of the cyber asset at the network element.

Systems and methods for evasive resiliency countermeasures

A device and method for context-aware, intelligent beaconing in a mission include: determining a current location of a beacon device; obtaining context information from one or more of a plurality of sensors, a database, a server, the beacon device, and external devices, wherein the context information includes behavior of the beacon device, and mission objectives; dynamically fusing the context information together to produce fused context information; dynamically setting a frequency for transmission of a beacon, based on the fused context information; and transmitting the beacon at the set frequency.

Context-aware, intelligent beaconing

Subject matter regards generating a 3D point cloud and registering the 3D point cloud to the surface of the Earth (sometimes called 'geo-locating'). A method can include capturing, by unmanned vehicles (UVs), image data representative of respective overlapping subsections of the object, registering the overlapping subsections to each other, and geo-locating the registered overlapping subsections.

Collaborative 3D mapping and surface registration

A system for data protection includes a first computing device comprising a security module; and a storage device coupled to the first computing device via a network interface. The security module comprises at least one of Software Root of Trust (SRoT) and Hardware Root of Trust (HRoT). The security module is further configured to: establish a trust channel between the first computing device and the storage device or storage service; monitor the first computing device and the storage device; create and enforce multi-dimensional data access control by tightly binding data access and permissions to authorized computing devices, users, applications, system services, networks, locations, and access time windows; and take over control of the storage device or storage service in response to a security risk to the system.

Adaptive, multi-layer enterprise data protection and resiliency platform

In some embodiments, a method for determining a location of an unmanned system (UMS) can include: receiving data from a plurality of data sources, wherein the data sources include a geolocation sensor and at least one of an RF receiver, a RADAR system, a LIDAR system, a SONAR system, an infrared camera, a Simultaneous Location and Mapping Algorithm (SLAM) system, an inertial sensor, or an acoustic sensor; determining a reliability of one or more of the data sources based on the received data; assigning weights to the data sources based at least in part on the determination of the reliability of the one or more data sources; and determining the location of the UMS using the received data and the assigned weights.

Intelligent location awareness for unmanned systems

A system for data protection includes a computing device comprising a processor, a Hardware Root of Trust (HRoT) module and a storage device. The HRoT device is configured to: validate integrity of the computing device; authenticate the computing device to communicate with the storage device; and take over control of storage device access and behaviour whenever suspicious or unauthorized data access from local or remote computing devices is detected. The HRoT device is further configured to, in response to detecting a security risk to at least one of the computing device and the storage device, block communication of the storage device.

Growing community of inventors

Bristow, VA, United States of America

Torsten Staab