Performance Analysis of Cross⁃Site Scripting Based on Natural Language Processing  

作　　者：Mengda Xu Luqun Li 

机构地区：[1]The College of Information,Mechanical and Electrical Engineering,Shanghai Normal University,Shanghai 200234,China

出　　处：《Journal of Harbin Institute of Technology(New Series)》2022年第4期19-25,共7页哈尔滨工业大学学报（英文版）

摘　　要：With the acceleration of network communication in the 5G era,the volume of data communication in cyberspace has increased unprecedentedly.The speed of data transmission will accelerate.Subsequently,the security of network communication data becomes more and more serious.Among them,malicious cross⁃site scripting leading to the leakage of user information is very serious.This article uses URL attribute analysis method and YARA rule to process data for cross⁃site scripting based on the long short⁃term memory(LSTM)characteristics of LSTM model.The results show that the LSTM classification model adopted in this paper has higher recall rate and F1⁃score than other machine learning methods,which proves that the method adopted in this paper is feasible.

关 键 词：cross⁃site scripting network communication web security natural language processing 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]