基于大數(shù)據(jù)的網(wǎng)絡(luò)異常行為檢測(cè)技術(shù)研究

摘要：文章所述方案充分發(fā)揮大數(shù)據(jù)處理技術(shù)與機(jī)器學(xué)習(xí)在網(wǎng)絡(luò)異常監(jiān)測(cè)中的優(yōu)勢(shì)，有效提升了網(wǎng)絡(luò)異常行為監(jiān)測(cè)的處理速度、準(zhǔn)確性，大大降低了誤報(bào)率，對(duì)大數(shù)據(jù)處理環(huán)境下網(wǎng)絡(luò)異常行為監(jiān)測(cè)具有一定的理論意義與現(xiàn)實(shí)應(yīng)用價(jià)值。

關(guān)鍵詞：大數(shù)據(jù)技術(shù)；網(wǎng)絡(luò)異常行為；技術(shù)研究

doi：10.3969/J.ISSN.1672-7274.2023.02.011

中圖分類號(hào)：TP 393.08               文獻(xiàn)標(biāo)示碼：A               文章編碼：1672-7274（2023）02-00-03

Research on Network Abnormal Behavior Detection Technology Based on Big Data

GAO Juxin

（Shanxi Institute of Applied Science and Technology， Lvliang 033000， China）

Abstract： The scheme described in this paper gives full play to the advantages of big data processing technology and machine learning in network anomaly monitoring， effectively improves the processing speed and accuracy of network anomaly behavior monitoring， and greatly reduces the rate of false positives. It has certain theoretical significance and practical application value for the monitoring of network abnormal behavior in the big data processing environment.

Key words： big data technology; network abnormal behavior; technical study

1  基于大數(shù)據(jù)的網(wǎng)絡(luò)異常行為檢測(cè)模型構(gòu)建

基于大數(shù)據(jù)的網(wǎng)絡(luò)異常分析模型通過提供大量安全數(shù)據(jù)的采集和存儲(chǔ)方案，以及分布式消息隊(duì)列、分布式離線分析組件以及流式處理組件，滿足數(shù)據(jù)收集和預(yù)處理、數(shù)據(jù)離線分析、數(shù)據(jù)流式處理、數(shù)據(jù)存儲(chǔ)等一系列需求。（剩余5404字）