An adversarial sample generation method for vehicle-mounted Ethernet flow space

By designing an adversarial example generation method in the vehicular Ethernet traffic space and using the particle swarm optimization algorithm to generate the optimal attack strategy, the problem of insufficient portability and practicality of adversarial examples in the vehicular environment in the existing technology is solved, and the efficient generation of adversarial examples to evaluate the robustness of intrusion detection systems is realized.

CN121037849BActive Publication Date: 2026-07-21NORTHEASTERN UNIV CHINA
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
NORTHEASTERN UNIV CHINA
Filing Date
2025-09-09
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing adversarial example generation methods cannot effectively evade intrusion detection systems in vehicular Ethernet environments, have poor portability and practicality, and the generation time increases linearly with the scale of malicious traffic, making it difficult to generate large-scale adversarial examples under limited prior knowledge.

Method used

A method for generating adversarial examples for the vehicular Ethernet traffic space is designed. Through an adversarial environment construction module, an optimal attack strategy generation module based on an optimization algorithm, and an optimal attack strategy generalization module, adversarial examples are generated in the traffic space using the particle swarm optimization algorithm to ensure that they can effectively evade the detection of intrusion detection systems.

Benefits of technology

It improves the portability and practicality of adversarial examples when evading different types of intrusion detection systems, increases generation efficiency, provides a method for generating adversarial examples that conforms to the threat capabilities of attackers, and evaluates the robustness of intrusion detection systems.

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Abstract

The application belongs to the technical field of vehicle network security, and discloses a kind of facing vehicle Ethernet flow space's countermeasure sample generation method, including countermeasure environment building module, optimal attack strategy generation module based on optimization algorithm and optimal attack strategy generalization module.A kind of representation method suitable for executing countermeasure attack in vehicle Ethernet flow space is proposed, which improves the practicability of countermeasure sample;The fitness function of particle swarm optimization algorithm is improved, and the transferability of countermeasure sample is enhanced;The best attack strategy generated on the representative template is generalized to large-scale flow, and the generation efficiency of countermeasure sample is improved.The method disclosed by the application can provide support for evaluating the robustness of intrusion detection system in vehicle network.
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