37 results about "Cyberphysical systems" patented technology

This document presents one or more advantageous approaches for Reinforcement Learning (RL) powered management of one or more transmission parameters, such as transmit power and diversity, for maximizing the application-layer reliability and availability of a Cyber-Physical System (CPS) with a minimized level of radio / power resource consumption. Example mathematical models are also disclosed and are useful for transforming high-level “intents” (e.g., KPIs that are applicable to industrial automation and control systems) into low-level orchestration objectives that drive the RL-based control. These objectives are subsequently employed in the definition of an RL-powered “orchestrator,” which may comprise an appropriately configured network node or other computing platform associated with the wireless communication network used to provide inter-device communications for a CPS comprising a population of devices. Further, the disclosure details example communication—e.g., observations and corresponding control signaling—between the orchestrator and the environment being managed.

Computer-implemented methods and systems for training an adversarial neural network to simulate a stealthy blind false data injection attack on a cyber physical system are provided. Supervised learning is used to generate an initial attack vector, by an adversarial attack generation model, based on inferred grid topology and historical measurements. A final attack vector is generated, by an adversarial verification model, based on a filtered subset of the initial attack vector utilizing a substitute bad data detection threshold, wherein the final attack vector enables creation of a counter measure.

An integrated cyber-physical system and method for high-fidelity distress monitoring and automated alert error mitigation. The system comprises a wearable multi-parametric sensing suite (100) for primary anomaly detection and an autonomous mobile robotic agent (200) for secondary contextual verification. Upon detection of a potential distress event (S110), the robotic agent (200) executes a priority undocking sequence (S120) from a charging station (500) to perform multi¬ modal acquisition (S130), including 3D skeletal pose estimation and acoustic sentiment analysis. A Cloud Processing Engine (300) synthesizes these data streams — including optional spatial occupancy data from an environmental sensor network (400) — to calculate a Validation Confidence Score (VCS) (S140) using a dynamic weighted fusion algorithm. This score enables the system to autonomously perform alert de-escalation (S150) for verified safe-states or execute prioritized escalation protocols (S160) to a caregiver interface (600) and an emergency services gateway (700). The invention effectively reduces alarm fatigue and improves emergency response reliability by providing contextual validation of biometric triggers.

The present invention relates to a cyber-physical system for optimizing a simulation model for chemical mechanical polishing based on actual measurement data of chemical mechanical polishing. The chemical mechanical polishing system includes a polishing apparatus (1) for polishing the workpiece (W) and an arithmetic system (47). The arithmetic system (47) includes a simulation model including at least a physical model configured to output an estimated polishing physical quantity including an estimated polishing rate of the workpiece (W). The arithmetic system (47) is configured to: input polishing conditions for the workpiece (W) into the simulation model; output the estimated polishing physical quantity of the workpiece (W) from the simulation model; and determine model parameters of the simulation model that bring the estimated polishing physical quantity closer to a measured polishing physical quantity of the workpiece (W).

We provide security measures that integrate and analyze information from cyberspace and physical space using generative AI. [Solution] A security support device 10 is provided, comprising: a cyber information collection means 150 for collecting anomaly information in cyberspace; a physical information collection means 160 for collecting anomaly information in physical space; a cyber-physical correspondence means 170 for associating anomaly information in cyberspace with anomaly information in physical space; a generation AI input / output means 110 for inputting the associated anomaly information in cyberspace and anomaly information in physical space as prompts to a generation AI 20 and obtaining security measures as a response from the generation AI 20; and a CPS integrated security measure determination means 120 for assigning priority and reliability to the security measures, which are the response from the generation AI 20, and transmitting them to a CPS (cyber-physical system) 30.

A method for determination of anomalies in a cyber-physical system (CPS) includes generating one or more diagnostic rules configured to calculate at least one auxiliary CPS variable. One or more values of the at least one auxiliary CPS variable are calculated for a predefined output interval of time based on collected values of a group of primary CPS variables for a predefined input interval of time based on the generated diagnostic rule. An anomaly is determined based on the collected values of the group of primary CPS variables and the one or more calculated values of the at least one auxiliary CPS variable.

The present invention relates to a method for error detection and handling in a DevOps-pipeline for a cyber physical system and related system. The method comprising the steps of: writing and committing code destined to be used for monitoring and / or controlling operations of components of the CPS; compiling the code and packaging it into deployable units; deploying the code per deployable unit into one or more component of the CPS; connecting one or more domain-specific language, DSL, elements to respective one or more CPS components; gathering data from the respective one or more CPS components by the one or more DSL elements; processing by the one or more DSL elements the data gathered in a format of the respective one or more CPS component; comparing by the one or more DSL element the processed data to a predefined failure condition to detect a failure.

One embodiment provides a system controller circuitry for mitigating a neurophysiological disorder. The system controller circuitry includes an optimization module, a feedback control module, and a model update module. The optimization module is configured to predict a sequence of control inputs based, at least in part, on a fractional order model of a neurophysiological system. A duration of the predicted sequence of control inputs corresponds to a prediction horizon. The feedback control module is configured to provide at least a portion of the sequence of control inputs to the neurophysiological system based, at least in part, on a current state of the neurophysiological system. A duration of the at least a portion corresponds to a control horizon. The model update module is configured to update one or more of a model parameter and / or an objective function parameter at an update interval, based, at least in part, on a recent state of the neurophysiological system.

A server can include an interface configured to receive sensor data relating to a cyber-physical system (CPS), as well as a processor. The processor can be configured to determine a performance parameter of the CPS from the sensor data; select a resource allocation strategy based on the performance parameter; execute an algorithmic process on at least a portion of the sensor data according to the resource allocation strategy; and control a transmitter to send data, representing an output of the executed artificial neural network, to the robot.

The application provides a resilient control method and system for denial of service attacks on networked physical systems, and relates to the field of security control of networked physical systems, and aims to solve the problem of non-periodic and boundaryless double-channel DOS attack. An event trigger generates an event when measurement data meets a specific trigger condition, transmits the trigger data, transmits the data under the condition of meeting the transmission rule, switches the observer to update the state estimation, and sends the estimation value to the controller; the controller sends an acknowledgement signal to the switching observer, calculates the control signal according to the estimation value, and sends the control signal to the actuator; the actuator feeds back the acknowledgement signal and executes the calculated control signal. Based on the event trigger mechanism, by designing a safe transmission strategy, a switching observer and a resilient control method, the state estimation and control of the networked physical system when suffering from double-channel independent DoS attack are realized, and the system stability is ensured and the communication resources are optimized.

The “Industrial Digestive System” encapsulates a novel paradigm in waste management and resource recovery, bridging the gap between sophisticated computational intelligence and industrial automation. The hardware component replicates the natural digestive system's efficiency in processing a diverse range of inputs, including municipal and industrial waste, transforming them into valuable outputs like biofuels, chemicals, and advanced composite / conglomerate materials. This process is achieved through a series of mechanized operations. Complementing the hardware, the software facet of the invention is rooted in advanced machine learning and optimization algorithms that optimize multivariable functions for the most efficient conversion of input to resources, orchestrating the transformation from varied waste streams, elements, and molecules into solid, liquid, and gaseous outputs. The result is an automated, intelligent manufacturing machine that enhances product quality and operational efficacy. “The Industrial Digestive System” can be seen as a new branch of cybernetics, a cyber-physical system inspired by nature.

The invention discloses an information and environment security risk identification method based on multi-modal data analysis, and aims to solve the problem that the'coupling risk 'of information security and environment security in a network-physical system is difficult to jointly identify. The method comprises the following steps: acquiring and aligning network side data and environment side data with timestamps and asset identifiers; outputting a network anomaly probability, an affected control object and a control instruction parameter by using a Transform network side security detection model; constructing two groups of boundary conditions of an abnormal control instruction and a baseline control instruction based on the affected control object, and performing conditional deduction in the physical information neural network model to obtain two environmental state prediction sequences; calculating an anti-fact deduction residual score according to the residual difference between the observation data and the two prediction sequences; and inputting the network side evidence and the environment side evidence into the micro evidence fusion model to obtain a coupling risk score and grade, and outputting a corresponding influenced control object, thereby realizing the technical effects of interpretable joint identification and grading early warning of the information security and environment security coupling risk.

An adaptive control method for cyber-physical systems (CPS) subjected to injection and deception attacks includes the following steps: S1: Constructing a control system model under a cyber-physical framework; S2: Defining actuator attacks when the system's sensors and actuators are subjected to adversary injection and deception attacks; S3: Defining sensor attacks when the system is subjected to sensor attacks; S4: Rewriting the system model under cyberattacks; S5: Based on the rewritten system model, obtaining the adaptive control law u using the BackStepping method; S6: Further deriving that all signals in the closed-loop system are globally bounded based on the adaptive control law u in S5, and designing a controller by introducing Nussbaum even functions and their variable derivatives. When the system is subjected to injection and deception attacks, the control parameters are adjusted to make the adjustment error arbitrarily small. This invention can ensure that the adjustment error can be arbitrarily small under injection and deception attacks by adjusting the control parameters.

A server may include an interface that is configured to receive sensor data related to a cyber-physical system (CPS); and a processor. The processor may be configured to determine a performance parameter of the CPS from the sensor data; select a resource allocation strategy based on the performance parameter; execute an algorithmic process on at least a portion of the sensor data according to the resource allocation strategy; and control a transmitter to send data representing an output of the executed artificial neural network to the robot.

Method for verification of a cyber-physical system (15) being controlled by a controller (2), the method comprising: - operating the system (15) starting from multiple different initial states; - detecting during operation a parameter value of at least one parameter describing the state of the system; - recording the parameter values at corresponding relative moments over time as a state time series (7) for each of the initial states; - determining at least one cross-sectional comprising the parameter values of the same relative moment in all of the state time series; - determining at least one convex body (8) based on a pre-defined proportion of the at least one cross-sectional; and - determining the reliability of the system (15) based on the at least one convex body (8).

A cyber-physical system for resilient monitoring and containment of electrical and computational infrastructure comprises distributed cyber-physical sentinel nodes configured to monitor electrical par

A method for operating a motor vehicle (20) comprising a bus system (3) via which data (5) are transmitted that influence at least one driving function of the motor vehicle (20), characterized in that data (5) relevant to the driving function are selected in a decision tree (30) in the form of influencing factors (31-36) and prioritized with respect to the driving function in order to significantly reduce the amount of data (5) to be transmitted via the bus system (3), wherein the motor vehicle (20) is considered as a cyber-physical system in its environment with all data (5) acquired in the motor vehicle (20) and its environment, wherein attributes with the greatest influencing factor (31-36) are extracted and explored, wherein data (5) from the environment of the vehicle (20) are structured as attributes of a layered model (17), wherein the decision tree (30) shows a weighting of certain attributes with respect to a malfunction of a driving function.

Systems and methods are provided for incident analysis in Cyber-Physical Systems (CPS) using a Temporal Graph-based Incident Analysis System (TGIAS) and / or Transition Based Categorical Anomaly Detection (TCAD). Dynamically gathered multimodal data from a distributed network of sensors across the CPS are preprocessed to identify abnormal sensor readings indicative of potential incidents, and a multi-layered incident timeline graph, representing abnormal sensor readings, relationships to specific CPS components, and temporal sequencing of events is constructed. Severity scores are calculated, and severity rankings are assigned to identified anomalies based on a composite index including impact on CPS operation, comparison with historical incident data, and predictive risk assessments. Probable root causes of incidents and pathways for anomaly propagation through the CPS are identified using causal interference and the incident timeline graph to detect underlying vulnerabilities and predict future system weaknesses. Recommended actions are generated and executed for incident resolution and system optimization.

A system for determining light conditions in a space of interest and to control a device thereon includes a light sensor arranged to detect light entering a sub-volume of the space of interest to provide measurement data corresponding to at least an intensity and direction distribution of light entering the sub-volume: a data processor configured to communicate with the light sensor to receive the measurement data, the data processor configured with a computational model to provide a calculated distribution of light based on the measurement date from the sub-volume of the space of interest; and a control system configured to communicate with the data processor to receive the calculated distribution of light and provide control signals based on the calculated distribution of light.

A qualitative and quantitative (Q2) method for verifying safety of movement of complex learning-enabled cyber-physical systems (Le-CPS) using a computer is provided. The method includes determining an initial set of states of the Le-CPS. The computer is used for determining a reachable set of the Le-CPS using a probstar reachability algorithm saved in memory of the computer. The computer includes a Q2 algorithm saved in the memory that is configured is used to simultaneously check (i) if the reachable set satisfies a predetermined safety constraint (qualitative verification) and (ii) determine a probability of satisfaction that the reachable set will satisfy the predetermined safety constraint (quantitative verification). Movement of the Le-CPS is planned based on the step of using the computer including the Q2 algorithm.

A method for detecting and attributing the cause of anomalies within a cyber-physical system such as in avionics or vetronics network is disclosed. The method comprises monitoring, via at least one processor, data of one or more components within the avionics and vetronics network in real time; determining, via the at least one processor, one or more anomalies from the monitored data using a condition-based maintenance model and a cyber-defense model; determining, via the at least one processor, whether the one or more anomalies is related to a cascading fault using the condition-based maintenance model and the cyber-defense model; determining, via the at least one processor, the one or more anomalies corresponding to a component failure or an evidence of the cyberattack; and generating, via the at least one processor, one or more alerts for a user associated with the one or more anomalies.

Systems and methods are provided for incident analysis in Cyber-Physical Systems (CPS) using a Temporal Graph-based Incident Analysis System (TGIAS) and / or Transition Based Categorical Anomaly Detection (TCAD). Dynamically gathered multimodal data from a distributed network of sensors across the CPS are preprocessed to identify abnormal sensor readings indicative of potential incidents, and a multi-layered incident timeline graph, representing abnormal sensor readings, relationships to specific CPS components, and temporal sequencing of events is constructed. Severity scores are calculated, and severity rankings are assigned to identified anomalies based on a composite index including impact on CPS operation, comparison with historical incident data, and predictive risk assessments. Probable root causes of incidents and pathways for anomaly propagation through the CPS are identified using causal interference and the incident timeline graph to detect underlying vulnerabilities and predict future system weaknesses. Recommended actions are generated and executed for incident resolution and system optimization.

The application discloses a network attack resilience constraint tracking control method for a network physical system and belongs to the network security field; the algorithm is aimed at a network physical system with uncertainty and possible network attacks, verifies the resilience of the controlled system to network attack inputs and other deception or mixed threat attacks through an original controller design, proposes three game rules of a non-cooperative game and two Stackelberg competitions to select optimal control related parameters, and proves that the optimal selection is unique in the three rules. The network physical system has the ability to resist network attack inputs and other deception or mixed threat attacks by using the method.

Methods for securing cyber-physical systems include attack generation systems, methods, and devices configured to assess vulnerabilities of cyber-physical systems include an example method of training an attack generative model using an attack policy to generate an attack dataset, training discriminators using a random attack dataset and generated attack dataset and training a generator using the trained discriminators.

Tracking of health and resilience of physical equipment and related systems are disclosed. A system includes physical equipment and one or more processors. The physical equipment includes one or more assets. The one or more processors are configured to determine a resilience metric for the physical equipment. The resilience metric includes a real power component and a reactive power component based, at least in part, on an aggregation of real components and reactive components of adaptive capacities of the one or more assets. A cyber-physical system includes physical equipment, network equipment configured to enable the physical equipment to communicate over one or more networks, a physical anomaly detection system (ADS) configured to detect anomalies in operation of the physical equipment and provide a physical component of a cyber-physical metric, and a cyber ADS configured to detect anomalies in network communications over the one or more networks.

Systems and methods for simulating cyber-physical systems are disclosed. A plurality of geographic simulation layers representing respective infrastructure sectors of a real-world environment may be generated, and the layers may be linked together with one another to create a multi-layer simulation. The associations between the layers of the simulation may be adjusted, and characteristics of the simulation layers themselves may be adjusted, to ensure that the simulation conforms to characteristics of the real-world environment being simulated. In some embodiments, a multi-user simulation system allows users at separate terminals to execute attack inputs and defense inputs against the simulation to try to destabilize and stabilize the simulation, respectively. Results of the attack inputs and defense inputs may be simultaneously displayed on a plurality of terminals.

An adaptive control system has sensors measuring field parameters of the interaction between an apparatus and its environment. A module determines, from the field parameters, whether the apparatus is

A system to protect an industrial asset includes a plurality of monitoring nodes each generating a data stream of current monitoring node values in time-domain, and a virtual agent associated with each of the plurality of monitoring nodes, the virtual agent being configured to detect anomalous performance of the corresponding monitoring node and configured to communicate with one or more other virtual agents via a network.

Disclosed herein are systems and methods for detection of anomalies in a cyber-physical system in real-time. In one aspect, an exemplary method comprises: obtaining, in real-time, randomly distributed stream of observations of CPS parameters; converting an observation of the CPS parameter to a uniform temporal grid (UTG); when at least a criterion for unloading at least one UTG node of the converted observations is satisfied, unloading the UTG nodes corresponding to the satisfied criterion; for each unloaded UTG node, calculating a value of each output CPS parameter of a set of output CPS parameters; and detecting an anomaly in the CPS based on the values of the output CPS parameters.