基于LVQ神经网络的反网络钓鱼技术研究简

随着网上金融和电子商务的迅速发展，在线购物、网上理财的用户数量急速上升，人们日益享受着互联网带来的便利，与此同时，以网上理财、在线购物等电子商务用户为主要攻击目标的网络钓鱼活动也迅速蔓延。网络钓鱼严重损害了网络用户以及网络服务提供商的利益，影响我国电子商务的发展。本文提出了一种基于LVQ神经网络的反钓鱼技术，通过综合分析钓鱼网址的URL特征和页面特征，并进行自动分类，取得了良好的检测效果。

Research of phishing website detection technology based on LVQ neural network

With the rapid development ofonline banking and e-commerce, the number ofusers increased gready. While people are enjoying the convenience brought by the Intemet, they also become the victims of phishing activities. Phishing harms the interests of Intemet users and network service providers seriously, and has a negative influence on the development of electronic commerce in our country. In this paper, we proposed an anti-phishing technique based on LVQ neural network by analyzing features extracted from suspected URLs and its pages, automatically classifying them into different categories and achieved good detection results.