New sensing technique for detecting application layer DDoS attacks targeting back-end database resources

D. Beckett, S. Sezer, J. McCanny
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引用次数: 9

Abstract

Distributed Denial of Service (DDoS) attacks targeting the application layer are becoming more prevalent due to a lack of suitable defence solutions. Existing research treats the web server environment as a black box, by only monitoring the edge network traffic; however, we believe that this approach limits the accuracy of the detection system as it does not protect the back-end database servers. In this paper we propose a new sensor located within the back-end system, which can produce additional database features. This allows for real-time insight into the actual database workload caused by each user enabling the detection of DDoS attacks targeting high database consumption resources. These resource metrics are analysed in real-time on a live website, using a decision tree classification engine. Our preliminary results show that a low rate asymmetric attack as low as 1 request every 10 seconds can be detected using these proposed features.
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针对后端数据库资源的应用层DDoS攻击检测新技术
由于缺乏合适的防御解决方案,针对应用层的分布式拒绝服务(DDoS)攻击变得越来越普遍。现有的研究将web服务器环境视为一个黑箱,只监控边缘网络流量;然而,我们认为这种方法限制了检测系统的准确性,因为它不保护后端数据库服务器。在本文中,我们提出了一个新的传感器位于后端系统,它可以产生额外的数据库特征。这允许实时了解由每个用户引起的实际数据库工作负载,从而检测针对高数据库消耗资源的DDoS攻击。使用决策树分类引擎,这些资源指标在实时网站上进行分析。我们的初步结果表明,使用这些建议的特征可以检测到低至每10秒1个请求的低速率非对称攻击。
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