Abstract: Described is a system for side-channel based detection of cyber-attack. In operation, the system converts data bus signals from a platform (e.g., vehicular platform) into a first time series of system states. The system further converts analog side-channel signals from the platform into a second time-series of system states. Anomalous behavior of the platform is detected by comparing the first time series of system states with the second time series of system states to identify violations of predetermined constraints. Upon detection, the anomalous behavior is designated as a cyber-attack of the platform, which causes the platform to initiate an action based on the detected cyber-attack. Such actions include implementing a safe made, etc.

Abstract: A system for cyber-attack detection within cyber-physical systems (such as a vehicle). The system operates by obtaining a time-varying analog side-channel signal from components with the cyber-physical system and converting the time-varying analog side-channel signal to a digital side-channel signal. A time-series of system states are then identified based on the digital side-channel signal. The time-series of system states are compared with software states as generated by the cyber-physical system components, such that when the software states are unmatched with the time-series of system states, a side-channel is designated as having a security breach. In such an event, the cyber-physical system is then caused to implement an action based on the side-channel security breach.

Abstract: A tracking system for tracking a moving target includes a processor and a tracking module that implements an iterative process for tracking the moving target. The iterative process includes receiving sensor data for a current state of the moving target. The process also includes applying a filter engine to the sensor data and a measure of error of a previous prediction of the current state of the target to produce a first estimate for an upcoming state and a first measure of error thereof. The process also includes receiving from at least one second tracking system, at least one second estimate for the upcoming state and second measure of error thereof. The process further includes defining a consensus estimate for the upcoming state and a consensus measure of error thereof using the first estimate and the at least one second estimate and the first and second measure of error thereof.

Abstract: Described is system for mapping user behavior to brain regions of interest. Using a cognitive-behavior model, a behavioral task is selected that is suited for a desired brain state. Using a functional-anatomical model coupled to the cognitive-behavior model, a set of high-definition neurostimulations is selected to be applied to the user during performance of the selected behavioral task. The selected set of high-definition neurostimulations targets specific regions of the user's brain. Changes in the user's brain state are sensed during application of the set of high-definition neurostimulations and performance of the selected behavioral task using at least one brain monitoring technique. The coupled functional-anatomical and cognitive-behavior models are adapted until the desired brain state is reached.

Abstract: Described is an inference circuit for pattern recognition for use within convolutional neural nets for online learning using K-means clustering. The inference circuit includes a set of templates, each template having a template data memory. The inference circuit also include at least one match element, the match element being operable for receiving an input data pattern and determining a degree of match between the input data pattern and a template. A best match logic circuit is included for selecting a template in the set of templates that best matches the input data pattern, said template being a best match template. Finally, an updated is included for probabilistically modifying the template data memories based on the best match template.

Abstract: Described is a system for secure database searching. The system comprises a client-server architecture which allows a client to securely search a database of records possessed by a server. A database query is generated by the client and transmitted to the server. The database query is processed by the server using a privacy-preserving search protocol. An encrypted match result is produced by the server without decrypting the database query. The encrypted match result is sent to the client, and the client decrypts the encrypted match result to obtain a set of block identifiers representing blocks of records in the database that match the database query. The client obtains a block of encrypted records containing match results using only the set of block identifiers. The match results are decrypted by the client using a key obtained from the server. The unencrypted match results to the database query are then output.

Abstract: An apparatus is provided for tracking a target moving between states using an iterative process. The apparatus receives sensor data for a current state i, and applies a cubature information filter and an H-infinity filter thereto to respectively produce an estimate for the upcoming state i+1 and a measure of error thereof, and adjust the measure of error. The apparatus then defines a consensus estimate of the upcoming state i+1 and a consensus adjusted measure of error thereof from the estimate and adjusted measure of error, and a second estimate and second adjusted measure of error that is received from at least one second apparatus tracking the target. The apparatus then applies a cubature information filter to the consensus estimate of the upcoming state i+1 and the consensus adjusted measure of error to predict the upcoming state i+1.

Abstract: Described is a system for self-organized critical image segmentation. During operation, the system generates a delta pattern from a self-organized critical process. An initial test pattern is then altered based on the delta pattern to generate a new test pattern. The new test pattern is a mask identifying distinct regions in an image. A new energy score is then generated of the new test pattern. The operations of generating the delta pattern and altering the initial test pattern are then repeated until an energy score of the new test pattern is less than an energy score of the initial test pattern. At that point, the initial test pattern is replaced with the new test pattern. Finally, the process is repeated until a termination condition is reached, at which point the new test pattern provides the image segmentation by dividing the image into distinct regions, including a foreground and background.

Abstract: Described is a system for detecting cyber intrusions based on analysis of network traffic. During operation, the system performs a statistical analysis of message timing on network traffic to produce a temporal dependency matrix representative of temporal dependency between different message types in the network traffic. The sets of temporal dependency matrices are decomposed into component matrices, where at least one component matrix represents typical properties of these matrices and at least one other component matrix represents atypical properties of the matrices. A new temporal dependency matrix is generated based on new network traffic. Finally, anomalous behavior is detected in the new network traffic by comparing component matrices of the new temporal dependency matrix with component matrices of the temporal dependency matrices under normal operation conditions.

Abstract: A system for cyber-attack detection within cyber-physical systems (such as a vehicle). The system operates by obtaining a time-varying analog side-channel signal from components with the cyber-physical system and converting the time-varying analog side-channel signal to a digital side-channel signal. A time-series of system states are then identified based on the digital side-channel signal. The time-series of system states are compared with software states as generated by the cyber-physical system components, such that when the software states are unmatched with the time-series of system states, a side-channel is designated as having a security breach. In such an event, the cyber-physical system is then caused to implement an action based on the side-channel security breach.

Abstract: Described is a system for inducing a desired behavioral effect using an electrical current stimulation. A brain monitoring subsystem includes monitoring electrodes for sensing brain activity, and a brain stimulation subsystem includes stimulating electrodes for applying an electrical current stimulation. Multi-scale distributed data is registered into a graphical representation. The system identifies a sub-graph in the graphical representation and maps the sub-graph onto concept features, generating a concept lattice which relates the concept features to a behavioral effect. Finally, an electrical current stimulation to be applied to produce the behavioral effect is determined.

Abstract: Described is a system for side-channel based detection of cyber-attack. In operation, the system converts data bus signals from a platform (e.g., vehicular platform) into a first time series of system states. The system further converts analog side-channel signals from the platform into a second time-series of system states. Anomalous behavior of the platform is detected by comparing the first time series of system states with the second time series of system states to identify violations of predetermined constraints. Upon detection, the anomalous behavior is designated as a cyber-attack of the platform, which causes the platform to initiate an action based on the detected cyber-attack. Such actions include implementing a safe made, etc.

Abstract: Described is a system for reducing the probability of large-scale failures in a transmission network. Tripped or damaged transmission lines in a transmission network are identified following a cascading failure. After each cascading failure, a subset of transmission lines is updated according to a specified rule to alter long-term dynamics of the transmission network such that the transmission network does not converge into a critical state.

Abstract: Described is a system for patient-specific rehabilitation that can be performed outside a clinic. The system monitors a patient in real-time to generate a quantitative assessment of a physical state and a motivational state of the patient using sensor data obtained from sensors. Predictions related to the patient are generated utilizing patient-specific biomechanical and neurocognitive models implemented with predictive simulations. Video feed of the patient is registered with sensor data and a set of simulation data. Rehabilitation guidance instructions are conveyed to the patient through dialog-based interactions.

Abstract: Described is system for mapping user behavior to brain regions of interest. Using a cognitive-behavior model, a behavioral task is selected that is suited for a desired brain state. Using a functional-anatomical model coupled to the cognitive-behavior model, a set of high-definition neurostimulations is selected to be applied to the user during performance of the selected behavioral task. The selected set of high-definition neurostimulations targets specific regions of the user's brain. Changes in the user's brain state are sensed during application of the set of high-definition neurostimulations and performance of the selected behavioral task using at least one brain monitoring technique. The coupled functional-anatomical and cognitive-behavior models are adapted until the desired brain state is reached.

Abstract: Described is a system for inducing a desired behavioral effect using an electrical current stimulation. A brain monitoring subsystem includes monitoring electrodes for sensing brain activity, and a brain stimulation subsystem includes stimulating electrodes for applying an electrical current stimulation. Multi-scale distributed data is registered into a graphical representation. The system identifies a sub-graph in the graphical representation and maps the sub-graph onto concept features, generating a concept lattice which relates the concept features to a behavioral effect. Finally, an electrical current stimulation to be applied to produce the behavioral effect is determined.

Abstract: Described is a system for system for gait intervention and fall prevention. The system is incorporated into a body suit having a plurality of distributed sensors and a vestibulo-muscular biostim array. The sensors are operable for providing biosensor data to the analytics module, while the vestibulo-muscular biostim array includes a plurality of distributed effectors. The analytics module is connected with the body suit and sensors and is operable for receiving biosensor data and analyzing a particular user's gait and predicting falls. Finally, a closed-loop biostim control module is included for activating the vestibulo-muscular biostim array to compensate for a risk of a predicted fall.

Abstract: Described is a system for generating an adaptable predictive model of the dynamics of a complex system, such as a vehicle. A set of current sensory data describing the vehicle's current state is collected from the vehicle. A set of predictive models is evaluated to identify a predictive model that best matches the vehicle's current state. If a predictive model is identified as a match, then the predictive model is adapted to better fit the vehicle's current state, resulting in an adapted predictive model. If a match is not identified, then a new predictive model is generated through automatic model learning using the current set of sensory data. The adapted predictive model or the new predictive model is then used to generate control outputs for the vehicle.

Abstract: A tracking system for tracking a moving target includes a processor and a tracking module that implements an iterative process for tracking the moving target. The iterative process includes receiving sensor data for a current state of the moving target. The process also includes applying a filter engine to the sensor data and a measure of error of a previous prediction of the current state of the target to produce a first estimate for an upcoming state and a first measure of error thereof. The process also includes receiving from at least one second tracking system, at least one second estimate for the upcoming state and second measure of error thereof. The process further includes defining a consensus estimate for the upcoming state and a consensus measure of error thereof using the first estimate and the at least one second estimate and the first and second measure of error thereof.

Abstract: An apparatus is provided for tracking a target moving between states using an iterative process. The apparatus receives sensor data for a current state i, and applies a cubature information filter and an H-infinity filter thereto to respectively produce an estimate for the upcoming state i+1 and a measure of error thereof, and adjust the measure of error. The apparatus then defines a consensus estimate of the upcoming state i+1 and a consensus adjusted measure of error thereof from the estimate and adjusted measure of error, and a second estimate and second adjusted measure of error that is received from at least one second apparatus tracking the target. The apparatus then applies a cubature information filter to the consensus estimate of the upcoming state i+1 and the consensus adjusted measure of error to predict the upcoming state i+1.