摘要
分析了网络钓鱼欺诈的现状,并对钓鱼检测常用的数据集和评估指标进行了总结。在此基础上,综述了网络钓鱼检测方法,包括黑名单策略、启发式方法、视觉匹配方法、基于机器学习的方法和基于自然语言理解的方法等,对比分析了各类方法的优缺点,进一步指出了钓鱼检测面临的挑战,并展望了钓鱼检测未来的研究趋势。
The current status of phishing scams were analyzed and the data sets and evaluation indicators commonly used in phishing detection were summaried. On this basis, a detailed overview of the typical methods of phishing detection was given, which included blacklist strategies, heuristic methods, visual matching methods, and methods based on machine learning and natural language processing. The comparison and analysis of those methods were given, and furtherly, the challenges and future trends of phishing detection were discussed.
作者
张茜
延志伟
李洪涛
耿光刚
ZHANG Xi YAN Zhi-wei LI Hong-tao GENG Guang-gang(Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China University of Chinese Academy of Sciences, Beijing 100049, China National Engineering Laboratory for Internet Domain Name Management, China Internet Network Information Center, Beijing 100190, China)
出处
《网络与信息安全学报》
2017年第7期7-24,共18页
Chinese Journal of Network and Information Security
基金
国家自然科学基金资助项目(No.61375039)~~
关键词
网络钓鱼欺诈
钓鱼检测
机器学习
视觉匹配
phishing fraud
phishing detection
machine learning
visual matching
