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...

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However, it is well known that GAN has the problems of mode collapse and

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