Network attack traffic generation method based on auxiliary classification type generative adversarial network

Abstract

The invention discloses a network attack traffic generation method based on an auxiliary classification type generative adversarial network, and the method can generate a malicious traffic sample which can cheat and escape from the detection of a defense system according to an existing network attack traffic data set sample by utilizing the principle of the generative adversarial network. The system comprises: a multi-source heterogeneous data fusion processing module which is responsible for defining a unified data format; a generator network which is responsible for generating a network statistical flow sample according to Gaussian noise and feedback from the discriminator; a discriminator network which is responsible for analyzing the attack traffic sample generated by the generator and the original network traffic sample, including authenticity analysis and attack traffic category analysis; and a classification fine tuning module which is responsible for debugging the performance of the generation model for generating specific types of traffic samples. According to the method, the network attack traffic generation model based on the auxiliary classification type generative adversarial network is constructed, the network attack traffic sample of a specific type can be generated according to the type of the network attack when the network traffic is generated, and the network attack can be simulated by generating the adversarial sample to detect the robustness of the existing intrusion detection system, and a new thought is provided for the existing traffic generator.

Description

technical field [0001] The invention relates to the fields of network security and industrial Internet network simulation, and specifically designs a method for generating network attack traffic based on an auxiliary classified generation confrontation network. Background technique [0002] With the continuous deepening of the research and application of the industrial Internet architecture, the key role of the traffic model in line with the actual situation in the performance evaluation of the new network architecture has become more and more obvious. The construction of complex multi-industry industrial Internet traffic characteristics security Testing traffic simulators is imperative. [0003] Due to the complex industrial Internet application scenarios, numerous dedicated protocols, and huge traffic data scale, in order to ensure the security of industrial Internet equipment, control, network, platform, and data, it is necessary to strengthen the security testing work fo...

AI Technical Summary

Problems solved by technology

Traditional network simulation tools (such as Cloudsim, OPNET, etc.) traffic modeling methods focus on application-specific traffic models and simplified traffic mixes, and cannot provide users with more information about virtual device data generation parameters and parameters according to the needs of different industrial application scenarios. Network parameter configuration

Moreover, it generally only supports modeling and simulation of a limited number of virtual devices and specific network environments, and the simulation performance of complex industrial application scenarios needs to be improved.

At the same time, these simulation tools consume too much time in the actual simulation process. The simulation of a simple application scenario may take a very long time because there is no simulation time compression mechanism, and the simulation efficiency is obviously insufficient.

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