Bastille Networks, Inc.

Bastille Network, Inc.

Michael Thomas Engle

Robert Baxley

Christopher Jay Rouland

David Maynor

Trung Dinh

Justin Trent Altman

Robert John Baxley

Systems and methods can support a sensor mesh and signal transmission architecture for electromagnetic signature analysis and threat detection. Sensor antennas may be deployed within an electromagnetic environment. A configurable antenna feed network can couple radio frequency signals from the antennas to both software-defined radio receivers and hardware-defined radio receivers. A raw signal analysis engine associated with the software-defined radio receiver can receive digital samples of the radio frequency signals, identify signal features within the digital samples, and generate signal feature vectors from the identified signal features. A signal feature network can receive the signal feature. A signal aggregation and analysis engine can receive the signal feature vectors from the signal feature network, aggregate the signal feature vectors, process the signal feature vectors, and identify wireless attacks according to the signal features within the signal feature vectors. One or more updatable analysis databases can support the signal processing operations.

Sensor mesh and signal transmission architectures for electromagnetic signature analysis

Systems and methods can support a computational signal processing architecture for electromagnetic signature analysis and threat detection. A plurality of sensor antennas can couple a radio frequency signal into a radio receiver. The radio receiver can generate digital samples of the signal. A raw signal analysis engine can identify signal features within the digital samples, generate signal feature vectors from the identified signal features, decode signal content from the signal feature vectors, and transmit the signal feature vectors into a signal feature network. The signal feature vectors may be aggregated from the signal feature network into a signal aggregation and analysis engine. The signal aggregation and analysis engine can refine feature vectors through processing such as identifying wireless attacks according to the signal features within the signal feature vectors. One or more operator interfaces and one or more analysis databases may support these operations.

Computational signal processing architectures for electromagnetic signature analysis

Systems and methods can support coprocessing radio signals and video to identify and locate a radio transmitter. Positions and orientations for cameras and RF sensors may be maintained. An RF signature associated with the radio transmitter may be received from the RF sensors to determine an RF persona. A first physical location for the radio transmitter may be estimated according to a physical radio propagation model operating on RF signals. A video stream from one or more of the cameras may be received. An individual may be identified in the video stream using computer vision techniques. A second physical location for the radio transmitter may be estimated from the video stream. Relationships may be established between the first physical location and the second physical location and between the RF persona and the identified individual. The relationships may be presented to an operator interface.

Diverse radio frequency signature, video, and image sensing for detection and localization

Systems and methods can support detecting and identifying threats associated with wireless devices. A radio receiver can collect radio frequency signals from one or more sensor antennas positioned within an electromagnetic environment. The receiver can generate data samples representing at least a portion of the radio frequency signals. Feature vectors can be generated comprising at least a portion of the data samples and attribute information. The attribute information can describe one or more features of a communicated signal within the radio frequency signals. Content of the feature vectors may be compared against signatures of known signals to identify radio frequency signals associated with a wireless attack. Content of the feature vectors may be compared against templates of known attacks to classify the identified wireless attacks. Threat information associated with the wireless attacks may be presented to one or more operator interfaces.

Electromagnetic signature analysis for threat detection in a wireless environment of embedded computing devices

Electromagnetic (EM)/radio frequency (RF) emissions may be detected and corresponding EM personas may be created. One or more EM personas may be associated with a super-persona corresponding to a particular entity. EM personas, super personas, and/or supplemental identifying information can be used to enforce security protocols.

Anomalous behavior detection based on behavioral signatures

Electromagnetic (EM)/radio frequency (RF) emissions may be detected and corresponding EM personas may be created. One or more EM personas may be associated with a super persona corresponding to a particular entity. EM personas, super personas, and/or supplemental identifying information can be used to enforce security protocols.

Electromagnetic persona generation based on radio frequency fingerprints

Systems and methods can support detecting and identifying threats associated with wireless devices within an electromagnetic environment. One or more sensor antennas may be located within the electromagnetic environment. Radio frequency signals may be coupled from the sensor antennas into a radio receiver. The radio receiver can communicate data samples representing a portion of the radio frequency signal to a raw signal analysis engine. The raw signal analysis engine can identify features associated with a communicated signal within the data samples. The raw signal analysis engine can classify modulation features and decode information features from the communicated signal. Feature vectors may be generated comprising the data samples and the identified features associated with the data samples. The feature vectors can be transmitted to a signal aggregation and analysis engine to support detecting and identifying electromagnetic threats and to support associated operator interfaces.

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Holmdel, NJ, United States of America

Michael Thomas Engle