A Parallel Acceleration Method of Network Intrusion Detection Based on KNN Algorithm

Abstract

A parallel acceleration method based on the KNN algorithm -based network invasion detection.Methods using CUDA parallel computing models. Firstly, parallel analysis was performed for network intrusion detection based on the KNN algorithm. When the distance from the calculation network invasion detection data point to the training data set, the general matrix multiplication function provided by CUDA was used to accelerate.Improving the operation speed; then, during the distance sorting stage, two types of parallelized sorting strategies have been provided. According to the sorting results of a small amount, the sorting algorithm with less sorting time can be selected for distance sorting;The classification stage of the point is based on the CUDA -based atom and plus operation.The experimental results show that the acceleration method proposed by the present invention is effective. Under the condition of ensuring the detection rate, it effectively improves the parallelization acceleration performance of network invasion detection.

Description

[0001] (1) Technical field [0002] The invention relates to a network intrusion detection technology in the field of information security, and is a parallelized acceleration method for network intrusion detection based on a KNN algorithm. [0003] (2) Background technology [0004] The purpose of network intrusion detection is to analyze the data traffic transmitted on the network, and find and detect abnormal traffic from it. At present, there are many classification algorithms used in network intrusion detection systems, among which network intrusion detection based on KNN (K-Nearest Neighbor) classification algorithm is the most commonly used. The most classic solution method of the KNN algorithm is the brute force search method. This method first calculates the distance of each network intrusion detection data point to the network intrusion detection training data set in turn, and then quickly sorts the distance of each intrusion detection data point in turn, thereby Get the k ...

AI Technical Summary

Problems solved by technology

[0009] The present invention first aims at the complex distance calculation problem in the KNN classification algorithm, extracts the common part of the calculation, and uses the general matrix multiplication function provided by CUDA to realize the distance calculation between the network intrusion detection data point and the network intrusion detection training data set , which improves the operation speed

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