计算机科学 ›› 2018, Vol. 45 ›› Issue (8): 141-145.doi: 10.11896/j.issn.1002-137X.2018.08.025

• 信息安全 • 上一篇    下一篇

基于KNN和GBDT的Web服务器指纹识别技术

南世慧1, 魏伟2, 吴华清1, 邹金蓉2, 赵志文1,2   

  1. 北京师范大学研究生院珠海分院 广东 珠海5190871
    北京师范大学信息科学与技术学院 北京1008752
  • 收稿日期:2017-05-09 出版日期:2018-08-29 发布日期:2018-08-29
  • 作者简介:南世慧(1993-),男,硕士生,主要研究领域为Web安全; 魏 伟(1993-),女,硕士生,主要研究领域为移动安全; 赵志文(1966-),男,博士,教授,博士生导师,主要研究领域为信息安全、云计算机安全,E-mail:zhaozw126@126.com(通信作者)。

Web Server Fingerprint Identification Technology Based on KNN and GBDT

NAN Shi-hui1, WEI Wei2, WU Hua-qing1, ZOU Jing-rong2, ZHAO Zhi-wen1,2   

  1. Zhuhai Branch,Graduate School of Beijing Normal University,Zhuhai,Guangdong 519087,China1
    School of Information Science and Technology,Beijing Normal University,Beijing 100875,China2
  • Received:2017-05-09 Online:2018-08-29 Published:2018-08-29

摘要: 现有的Web服务器指纹识别方法容易因响应头被篡改而得不到准确的识别结果,而且已有的基于机器学习的相关识别方法需要预先发送大量的请求来进行识别。针对上述问题,通过分析响应头的特征关系,提出一种基于KNN和GBDT的Web服务器指纹识别算法,其只需要发送两种不同类型的异常请求,就能识别对应的Web服务器指纹类型和版本范围。与已有Web服务器指纹识别算法进行的对比实验结果表明,所提算法的识别速度和准确率均得到了优化。

关键词: Web指纹, 集成学习, 梯度提升决策树, 网络安全

Abstract: Conventional Web server fingerprinting method is easy to modify the response head so that the recognition result is not accurate,and the existing recognition method based on machine learning needs to send a large number of requestsfor identification.To solve these problems,by analyzing the feature relations of the response head,a Web server fingerprint recognition algorithm based on KNN and GBDT was proposed.Only two different types of exception requests are sent to identify the corresponding Web server fingerprint type and version range.Compared with the existing algorithm of the relevant Web server fingerprint recognition,the proposed algorithm can optimize the recognition speed and the recognition accuracy.

Key words: Cyber security, Ensemble learning, Gradient decision boosting tree, Web fingerprint

中图分类号: 

  • TP393
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