【摘要】 由于Web技术的不断发展,尤其是5G技术的逐渐普及,万物联网的时代已经到来.网络的便利让数据的流通更加的及时和有价值,各种Web应用不仅方便了人们的日常生活,推进了社会的进步,更是带来了巨大的经济效益.因此,许多不法分子以攻击他人Web应用的方式来获取盈利,而作为OWASP(Open WebApplication Security Project)公布的报告中排名第一的注入类漏洞,是不法分子最常攻击的方向,带来了巨大的安全威胁.近年来,众多安全研究者都着力于找寻出更高效,准确度更高的方式来防御SQL注入攻击,本文将会对当前研究状况进行总结分析,并提出一种新基于LSTM神经网络的SQL注入语句分类识别模型.更多还原

【Abstract】 Due to the continuous development of Web technologies, especially the gradual popularization of 5 G technology,the era of the Internet of Things has arrived. The convenience of the network makes the circulation of data more timely and valuable. Various network applications not only facilitate people’s daily life,but also promote the progress of society and bring huge economic benefits. As the top one injection class vulnerability in the report published by OWASP(Open Web Application Security Project),is the most common direction of attack by criminals,and has brought a huge security threat. In recent years,many security researchers have focused on finding more efficient and accurate ways to defend against SQL injection attacks. This paper will summarize the current research situation and propose a new SQL injection statement classification recognition model based on LSTM neural network.更多还原