Metalearning-based small sample Wi-Fi camouflage attack detection method and system

Abstract

A small sample Wi-Fi forgery attack detection method based on meta-learning comprises the following steps: 1) data preprocessing: converting network traffic features into images, wherein the number of image channels is consistent with the hierarchical features of a protocol framework; and performing thermal coding processing on data labels; 2) deep feature extraction: processing data by using a convolutional neural network, and extracting spatial structure features; inputting the original features and the extracted features into a plurality of fully connected layers, and finally outputting a prediction task label; 3) meta-knowledge transfer of multiple auxiliary networks: constructing multiple auxiliary networks to learn meta-knowledge from historical WAID tasks to quickly adapt to new tasks; 4) method evaluation: randomly selecting two types from the three types to form a historical WAID task, and selecting a normal sample and a remaining new attack type to construct a new WAID task. The invention also comprises a system for detecting the small sample Wi-Fi forgery attack based on meta-learning. The method is suitable for the situation of few samples, and meets the requirements of resource constraint and real-time performance of the Internet of Things.

Description

technical field [0001] The invention relates to the security field of the Internet of Things, and relates to a meta-learning-based few-sample learning detection method and system. Background technique [0002] In recent years, the number of Internet of Things (IoT) smart devices has increased dramatically, leading to a significant increase in wireless network traffic. By 2021, wireless network traffic has accounted for two-thirds of global network traffic, of which 66% is generated by Wi-Fi (such as IEEE802.11 networks) and cellular networks. By 2023, there will be nearly 628 million public Wi-Fi hotspots worldwide, up from 169 million in 2018, a fourfold increase. Widely deployed Wi-Fi networks provide convenient and high-speed LAN communications, but they are also accompanied by privacy and security issues such as Wi-Fi masquerading, injection, and flooding attacks. [0003] For the purpose of Wi-Fi impersonation attack detection (WAID), intrusion detection (Intrusion de...

AI Technical Summary

Problems solved by technology

However, it is well known that GAN has the problems of mode collapse and sample retraining, which is difficult to apply to the actual environment.

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