作者
Vinayaka Jyothi, Xueyang Wang, Sateesh K Addepalli, Ramesh Karri
发表日期
2016/1/4
研讨会论文
2016 29th international conference on VLSI design and 2016 15th international conference on embedded systems (VLSID)
页码范围
587-588
出版商
IEEE
简介
Denial-of-Service (DoS) and Distributed Denial-of Service (DDoS) attacks account for one third of all service downtime incidents. Current DoS/DDoS attacks are not only limited to knocking down online services, but they also disguise other malicious attacks such as delivering malware, data-theft, wire fraud and even extortion. Detection of these attacks is predominantly based on the packet data and metrics derived only from packets. This work proposes a host based DDoS detection framework called BRAIN: BehavioR based Adaptive Intrusion detection in Networks. BRAIN leverages already available Hardware Performance Counters in modern processors to model the application behavior using low-level hardware events. BRAIN combines network statistics and modeled application behavior to detect DDoS attacks using machine learning. Our experiments show that BRAIN can detect multiple types of DDoS …
引用总数
201620172018201920202021202220232024456109151275
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