Drone Security Verification in IIoT Using Hierarchical Petri-Net Modeling
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Solution Overview
Problem
In industrial Internet of Things (IIoT) systems, drones pose a risk due to their ability to behave unpredictably, potentially disrupting system operations, necessitating a method to verify if they adhere to preset methods or deviate from them.
Innovation Solution
A method using petri net modeling to create a hierarchical type petri net model of the IIoT system, which includes determination factors to assess whether the drone's operation is abnormal, such as communication hindrance, altered waypoints, enforced clustering, capture, access control, and authorization, thereby identifying security vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If drone is used as independent entity in IIoT system, then system flexibility and communication capability are improved, but system reliability and security are worsened due to unpredictable drone behavior
Solution Approach 1:
The patent implements a verification mechanism that continuously monitors drone behavior against preset methods and provides feedback when anomalies are detected. The system observes drone operations, compares them with expected behavior patterns, and triggers security responses when deviations occur, thereby maintaining reliability while preserving communication flexibility.
Solution Approach 2:
The patent establishes preset behavior methods and verification criteria before drone operations begin. By pre-defining acceptable behavior patterns and verification rules, the system prepares security measures in advance, enabling rapid response to potential security threats without compromising ongoing communication operations.
2Reliability
If comprehensive verification of drone behavior is performed, then security vulnerability detection is improved, but system overhead and resource consumption increase
Solution Approach 1:
The patent extracts only the essential verification factors needed for security assessment from the complete drone operation dataset. By identifying and monitoring only critical behavior parameters (such as communication patterns, position changes, and authorization status) rather than all operational data, the system achieves effective security detection while minimizing processing overhead and resource consumption.
3Measurement precision
If multiple determination factors are monitored for drone verification, then verification accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the verification process into multiple independent determination factors (communication verification, position verification, authorization verification, etc.). Each factor is evaluated separately using simple comparison logic against preset criteria, then combined to form the overall verification result. This segmentation maintains high verification accuracy while keeping each individual verification component simple and manageable.
Data Source
AI summary
A method for verifying a drone included in an industrial Internet of Things (IIoT) system, using a petri-net modeling is disclosed. In an embodiment, the method includes a step of modeling the IIoT system as a hierarchical petri-net (modeling step); and a step of verifying whether the drone has security vulnerability on the basis of the hierarchical petri-net model (verification step), wherein the verification step can determine that a drone has security vulnerability when at least one of a plurality of determination factors provided as places to the hierarchical petri-net model determines that the drone is operating abnormally.