面向网站图像数据的安全分析系统

随着网络大众媒体的出现与流行，产生了文字、图像、视频等各种类型的海量数据，这对于相关内容审查工作提出了严峻挑战，尤其是图像数据的内容审核与安全等更为困难.但目前针对图像数据的安全分析并不成熟，并且不法分子时常对正常运营的网站进行攻击，将合法图像篡改为违规图像，这严重危害网络安全.本文针对这一实际应用需求，设计并实现了一个面向网站图像数据的安全分析系统，该系统主要包括以下两个模块：（1）基于深度学习的图像内容检测引擎模块；（2）基于事件触发技术及外挂轮询技术的图像防篡改模块.该系统可快速审查图像数据内容是否合法并且自动监测图像数据是否被篡改.

Security Analysis System for Web Images Data

With the advent and popularization of Internet mass media, massive data have been generated in forms of texts, images, videos, etc. This poses a serious challenge for the review of related content, especially the security review of the image data. At present, the safety analysis of image data is not mature and thus criminals often hack websites and tamper with the images on the websites, which poses significant threats to network security. Targeted at this practical application, this study designs and implements a web image data security analysis system, which is composed of two major modules:(1) illegal image detection engine module based on deep learning algorithm; (2) image tamper-proof module based on event trigger technology and plug-in polling technology. The system can quickly review whether the image data content is legitimate and automatically monitor whether the image data has been tampered with.