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A Precise and Autonomous System for the Detection of Insect Emergence Patterns

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Published on: January 9, 2019

Insertion attack identification in discrete event systems using petri nets with an observer.

Adeeb A Ahmed¹, Yufeng Chen¹, Ahmed M El-Sherbeeny²

¹Control Science and Engineering Department, School of Electro-Mechanical Engineering, Xidian University, Xi'an, China.

|December 9, 2024

Summary

This study introduces a new method for detecting sensor attacks in discrete event systems using Petri nets. The approach precisely identifies insertion attacks by monitoring tokens in a specially designed observation place.

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Area of Science:

Computer Science
Control Theory
Cybersecurity

Background:

Discrete event systems (DES) are susceptible to sensor attacks that compromise system integrity.
Petri nets are a common modeling tool for DES, but modeling and detecting sensor attacks require advanced techniques.
Insertion attacks, a type of sensor attack, can manipulate system states and mislead observers.

Purpose of the Study:

To develop a novel framework for modeling and identifying sensor attacks, specifically insertion attacks, in discrete event systems using Petri nets.
To enhance the robustness and accuracy of attack detection mechanisms in secure discrete event systems.

Main Methods:

Formulation of a novel observation structure to systematically model insertion attacks within the Petri net framework.
Generation of an extended reachability graph incorporating the observation structure to identify critical markings.
Computation of an observation place using integer linear programming for precise attack occurrence detection.

Main Results:

The proposed method accurately detects attack occurrences by analyzing the number of tokens in the designed observation place.
The approach successfully models insertion attacks within the Petri net framework, even with negative markings.
Experimental verification confirms the effectiveness of the developed approach.

Conclusions:

The novel observation structure and integer linear programming formulation provide a precise and robust method for identifying sensor attacks in discrete event systems.
The approach offers enhanced detection accuracy and robustness compared to existing techniques, advancing the field of secure discrete event systems.