Intelligent Fusion Technology, Inc.

Sixiao Wei

Genshe Chen

Erik Philip Blasch

Khanh D Pham

Bin Jia

Dan Shen

Zhijiang Chen

Carolyn Sheaff

Xin Tian

Gang Wang

Yi Li

Kui Liu

Haibin Ling

Lun Li

Yiran Xu

Zhengyang Fan

A method for detecting GPS spoofing attacks includes providing a trained deep learning (DL) model based on neural networks, feeding GPS signals into the trained DL model, using asymmetric Shapley values (ASVs) to calculate feature contributions, using the ASVs to assign a non-uniform distribution over an ordering of features, obtaining causal structures among the features, applying the ASVs to causal Shapley additive explanation to obtain Shapley attributions, incorporating the Shapley attributions and the causal structures, and detecting GPS spoofing attacks by running the trained DL model and using the causal structures, non-uniform distribution, feature contributions, and Shapley attributions.

Systems and methods to detect GPS spoofing attacks

Various embodiments provide a method for free space optical communication performance prediction method. The method includes: in a training stage, collecting a large number of data representing FSOC performance from external data sources and through simulation in five feature categories; dividing the collected data into training datasets and testing datasets to train a prediction model based on a deep neural network (DNN); evaluating a prediction error by a loss function and adjusting weights and biases of hidden layers of the DNN to minimize the prediction error; repeating training the prediction model until the prediction error is smaller than or equal to a pre-set threshold; in an application stage, receiving parameters entered by a user for an application scenario; retrieving and preparing real-time data from the external data sources for the application scenario; and generating near real-time FSOC performance prediction results based on the trained prediction model.

Method and system for free space optical communication performance prediction

Methods and systems for space situational awareness (SSA) demonstration are provided. The system includes a space data collector component, for collecting space initialization data of space objects from initialized space sources and pre-processing the space initialization data; a data relocation component, for distributing the space initialization data pushed from the space data collector component into multiple streaming channels for streaming; a streaming platform, for streaming, mapping, and reducing the space initialization data from the data relocation component to provide streamed data; a real-time analysis component, for calculating the streamed data to conduct a real-time detecting and tracking analysis of the space objects by implementing algorithms for one or more of space uncertainty propagation, space object tracking, sensor management, and collision avoidance; and a space visualization component, for displaying a visualization of space situational awareness (SSA) based on analyzed results from the real-time analysis component.

System and method for space situational awareness demonstration

Methods and systems for cyber secure data communications are provided. In some embodiments, a method for transmitting data comprises: performing a marker-based data encoding process to embed a digital watermark into each of a plurality of original data flows to be transmitted to a plurality of receivers; performing a non-orthogonal multiple access process to allocate transmission powers to the plurality of original data flows, such that the plurality of original data flows are simultaneously superposed on a carrier frequency to generate a superposed signal; performing a noise modulation process to modulate the superposed signal to generate a noise-like signal and a reference noise signal; transmitting the noise-like signal and the reference noise signal through orthogonally polarized antennas; and performing a portal-based data integrity analysis process to check whether a receiver in the plurality of receivers is compromised or manipulated.

Methods and systems for high throughput and cyber-secure data communications

Method and system for detecting and tracking multiple moving targets based on wide-area motion imagery are provided. The method includes receiving a task request from a client; sending the task request to a local agent; acquiring to-be-processed images from the client, in response to the task request; calling an Hadoop API and checking a running status of a Hadoop system for an available resource in the Hadoop system; when a resource in the Hadoop system is available, pushing the to-be processed images to a back-end Hadoop distributed file system (HDFS); running tracking algorithms of multiple moving objects associated with the to-be-processed images to provide tracking results of the multiple moving objects; when the Hadoop system is completed in running the tracking algorithms, generating and sending a message to the local agent; and sending the tracking results of the multiple moving objects from the HDFS to the front-end database.

System and method for detecting and tracking multiple moving targets based on wide-area motion imagery

In accordance with various embodiments of the disclosed subject matter, a method and a system for detecting multiple objects from real-time images are provided. The method comprises: performing, using a CPU host, an image segmentation process to divide real-time input images into a plurality of image partitions; performing, by multiple GPUs, a fast block-wise registration process, a mark setting process, a background generation process, a foreground generation process based on a Hyper-Q computation infrastructure, and a support vector machine classification process; and generating, by the CPU host, visualization classification images.

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Germantown, MD, United States of America

Sixiao Wei