首页> 外文会议>IEEE International Conference on Computer and Communications >DDoS detection and prevention based on artificial intelligence techniques
【24h】

DDoS detection and prevention based on artificial intelligence techniques

机译:基于人工智能技术的DDoS检测与预防

获取原文

摘要

DDoS attacks have been the major threats for the Internet and can bring great loss to companies and governments. With the development of emerging technologies, such as cloud computing, Internet of things, artificial intelligence techniques, attackers can launch a huge volume of DDoS attacks with a lower cost, and it is much harder to detect and prevent DDoS attacks. Because DDoS traffic is similar to normal traffic. Some artificial intelligence techniques like machine learning algorithms have been used to classify DDoS attack traffic and detect DDoS attacks, such as Naive Bayes and Random forest tree. In the paper, we survey on the latest progress on the DDoS attack detection using artificial intelligence techniques and give recommendations on artificial intelligence techniques to be used in DDoS attack detection and prevention.
机译:DDoS攻击已成为Internet的主要威胁,可能给公司和政府带来巨大损失。随着云计算,物联网,人工智能技术等新兴技术的发展,攻击者可以以较低的成本发起大量的DDoS攻击,而检测和预防DDoS攻击则变得更加困难。因为DDoS流​​量类似于正常流量。一些人工智能技术(例如机器学习算法)已用于对DDoS攻击流量进行分类并检测DDoS攻击,例如朴素贝叶斯(Naive Bayes)和随机森林树(Random forest tree)。在本文中,我们调查了使用人工智能技术进行DDoS攻击检测的最新进展,并提出了有关将用于DDoS攻击检测和预防的人工智能技术的建议。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号