DETAILED ACTION
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This Office Action is in response to the communication filed on 05/21/2026.
Claims 1-13 have been amended.
Claims 1-13 are pending for consideration.
Response to Arguments
Regarding the 112 2nd rejection of claims 1-13, Applicant has amended these claims. Therefore, the rejection has been withdrawn.
Regarding the nonstatutory double patenting rejection of claims 1-13, Application No. 18/694,040 has been abandoned. Therefore, the rejection has been withdrawn.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-13 are rejected under 35 U.S.C. 103 as being unpatentable over Zarur et al. (U.S. 2022/0027529)(hereinafter Zarur) in view of Eckhart et al. ("A Specification-based State Replication Approach for Digital Twins")(hereinafter Eckhart).
Regarding claims 1, 6, 7, 11, and 13, Zarur teaches A computer-implemented method for identifying manipulations of cyber-physical-systems, in which, comprising: a) providing a cyber-physical system having an embedded, distributed, and complex system structure including: system processes and system components communicating in a technical context via a network using communication technology and communication protocols (Zarur: see Fig. 1), at least one Programmable Logic Controller (PLC) (Zarur: see Page 9 paragraph 0113, "Industrial device 302 may be, for example, an industrial controller (e.g., a programmable logic controller or other type of programmable automation controller) configured to execute an industrial control program 704 to facilitate monitoring and control of an industrial machine or process") configured to control and/or regulate the cyber-physical system, the PLC being connected via sensors and/or actuators with controllable system processes and controllable system components (Zarur: see Page 4 paragraph 0072, " Industrial devices 120 may include input devices that provide data relating to the controlled industrial systems to the industrial controllers 118, output devices that respond to control signals generated by the industrial controllers 118 to control aspects of the industrial systems, or devices that act as both input and output devices. Example input devices can include telemetry devices (e.g., temperature sensors, flow meters, level sensors, pressure sensors, etc), manual operator control devices (e.g., push buttons, selector switches, etc.), safety monitoring devices (e.g., safety mats, safety pull cords, light curtains, etc.), and other such devices"), wherein the sensors and/or the actuators generate corresponding sensor/actor-signal-information utilized by the PLC for the control and/or regulation (Zarur: see Page 4 paragraph 0073, "The controller I/O can communicate with a controller's processor over a backplane such that the digital and analog signals can be read into and controlled by the control programs"), wherein the cyber-physical system provides the sensor/actor-signal-information depicting a behavior of the cyber-physical system during operation or commissioning (Zarur: see Page 28 paragraph 0239, "Simulation component 2908 generates digital and analog I/O values representing, for example, sensor outputs, metering outputs, or other data analogous to the data expected to be generated by the physical transport system based on the design and operating characteristics encoded in the model 3002");
wherein the cyber-physical system provides the sensor/actor-signal-information depicting a behavior of the cyber-physical system during operation or commissioning (Zarur: see Page 28 paragraph 0239, "Simulation component 2908 generates digital and analog I/O values representing, for example, sensor outputs, metering outputs, or other data analogous to the data expected to be generated by the physical transport system based on the design and operating characteristics encoded in the model 3002"); b) operating a digital twin unit, which for model-based digital twin representation of the cyber-physical system is assignable via at least one of a human-machine-interface unit and a Supervisory Control and Data Acquisition (SCADA) unit to the PLC, such that based on a simulation model of the cyber-physical system and on an emulated PLC, a digital twin is created and executed, which replicates the behavior of the cyber-physical system and consequently produces replicated sensor/actor-signal-information by simulating the cyber-physical system (Zarur: see Page 4 paragraph 0074, " Industrial automation systems often include one or more human-machine interfaces (HMIs) 114 that allow plant personnel to view telemetry and status data associated with the automation systems, and to control some aspects of system operation. HMIs 114 may communicate with one or more of the industrial controllers 118 over a plant network 116, and exchange data with the industrial controllers to facilitate visualization of information relating to the controlled industrial processes on one or more pre-developed operator interface screens"; Page 14 paragraph 0147, "If the automation model—embodied by asset model 422—can be linked to the mechanical model 1504 such that contextualized data can be shared between the two models, the resulting composite model can serve as a digital twin 1506 of the industrial asset 1502 that, when provided with real-time or historical smart object data generated by the industrial asset 1502 being modeled, holistically describes real-time or historical behavior of the industrial asset 1502"); wherein, when the cyber-physical system and the digital twin unit are run in parallel (Zarur: see Page 18 paragraph 0177, "According to another type of application, digital twin 1506 can be analyzed in parallel with its corresponding real-world industrial asset and the results of this analysis can be used to perform supplemental supervisory control of the asset or for reporting purposes") and the detected deviation exceeds a predetermined threshold or tolerance value (Zarur: see Page 29 paragraph 0247, "Accordingly, the steady state can be defined as the point in time when the change of the variance of these performance aspects falls within a defined threshold. After reaching this steady state operation, the metrics accumulated prior to reaching the steady state (that is, the performance during the transient operation) can be cleared to eliminate the influence of this transient operation and the test can be restarted. In some embodiments, the simulation component 2908 can conclude the simulation session when all metrics variances are within a defined threshold (which may be a user-defined threshold)").
However, Zarur does not teach c1) cyclically detecting a deviation in the behavior of the cyber-physical system by comparing the sensor/actor-signal-information with the replicated sensor/actor-signal-information; c2) identifying a manipulation of the cyber-physical system if for each detection cycle the sensor/actor-signal-information and the replicated sensor/actor- signal-information are different and consequently the deviation is detected.
Nevertheless, Eckhart-which is in the same field of endeavor- teaches c1) cyclically detecting a deviation in the behavior of the cyber-physical system by comparing the sensor/actor-signal-information with the replicated sensor/actor-signal-information (Eckhart: see Section 4.3.1 algorithm 1 lines 4-24; Section 4.2.6, "Based on this assumption, comparing the inputs and outputs of the physical environment with those of the virtual one may reveal either device faults or malicious activity. Supplementary, the states of digital twins can also be factored into the comparison in order to consider physical process states"); and c2) identifying a manipulation of the cyber-physical system if for each detection cycle the sensor/actor-signal-information and the replicated sensor/actor- signal-information are different and consequently the deviation is detected (Eckhart: see Section 4.2.6, "Assuming that the specification of the CPS precisely describes the correct behavior and each digital twin follows the state of its physical counterpart, a divergence between the physical and virtual environment should be detectable. Based on this assumption, comparing the inputs and outputs of the physical environment with those of the virtual one may reveal either device faults or malicious activity").
Zarur and Eckhart are analogous art because they are from the same field of endeavor. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine Zarur’s digital twin simulation and testing model to predict performance metrics of an industrial automation system with Eckhart’s cyber-physical intrusion detection system. The suggestion/motivation for doing so would be simulate deviated data on a system by replicating the environment and evaluating the systems ability to recover from an intrusion.
Regarding claims 2 and 8, Zarur teaches a source of the manipulation identified by the deviation detection is determined or localized by applying a root-cause-analysis, in which dependencies between the sensor/actor-signal-information are analyzed, considering that the dependencies between the sensor/actor-signal-information changeover time according to an operation point the cyber-physical system is currently in, the dependencies between the sensor/actor-signal-information are derived inside the network, the system processes, and the system components by partial derivatives of the simulation model, and the dependencies between the sensor/actor-signal-information inside the PLC are derived either by analyzing, PLC- codes or by analyzing formalized flow-diagrams of the cyber-physical system (Zarur: see Page 35 paragraph 0291, "Analytics component 2912 can also analyze past and present BIDT data 4908 together with the system properties encoded in the automation model 3002 or digital twin 4802 in order to identify root causes of operational problems, such as deviations from expected transport system behavior").
Regarding claims 3 and 9, Zarur teaches manipulation-effects on the cyber-physical system are examined to check whether countermeasures, are appropriate to protect the cyber-physical system with regard to the manipulation either identified by the deviation detection or identified by the deviation detection and determined or localized by the root-cause-analysis, and which one thereof, come into question, are possible, or could be taken by assigning the manipulation to the digital twin, where according to a fast-forward simulation mechanism, it is simulated what happens to the cyber-physical system as a result of the assigned manipulation, and an optimization algorithm applied to the fast-forward simulation mechanism or a what-if algorithm applied multiple times to the fast-forward simulation mechanism, it is evaluated by which countermeasure the manipulated cyber-physical system is returned to a safe state (Zarur: see Page 28 paragraph 0242, "This simulation technique can allow the user to view potential mover throughput problems, such as instances of station starvation or congestion at certain segments of the transport system at certain times. The user may also recognize possible causes of throughput problems based on visual examination of the animated simulation. In this way, the user can test and evaluate the proposed LSM transport system design prior to building the transport system. During this stage of the design and testing phase, the model 3002 can run as a complete virtualization and emulate the controls behavior").
Regarding claims 4 and 10, Zarur teaches the predetermined threshold or tolerance value is a default value (Zarur: see Page 29 paragraph 0247, "In some embodiments, the simulation component 2908 can conclude the simulation session when all metrics variances are within a defined threshold (which may be a user-defined threshold)").
Regarding claims 5 and 12, Zarur teaches the cyber-physical system is a production or industrial plant (Zarur: see Page 3 paragraph 0071, " FIG. 1 is a block diagram of an example industrial environment 100. In this example, a number of industrial controllers 118 are deployed throughout an industrial plant environment to monitor and control respective industrial systems or processes relating to product manufacture, machining, motion control, batch processing, material handling, or other such industrial functions").
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KELAH JANAE MCFARLAND-BARNES whose telephone number is (571)272-5953. The examiner can normally be reached Monday through Friday 8:00am until 4:00pm Central Time.
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/KELAH JANAE MCFARLAND-BARNES/Examiner, Art Unit 2431
/LYNN D FEILD/Supervisory Patent Examiner, Art Unit 2431
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