As network attacks have increased in number and severity over the past few years, intrusion detection system (IDS) is increasingly becoming a critical component to secure the netwo...
A low-effort data mining approach to labeling network event records in a WLAN is proposed. The problem being addressed is often observed in an AI and data mining strategy to netwo...
Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliy...
Machine learning systems are deployed in many adversarial conditions like intrusion detection, where a classifier has to decide whether a sequence of actions come from a legitimat...
Benjamin Liebald, Dan Roth, Neelay Shah, Vivek Sri...
Abstract. Eight sites participated in the second DARPA off-line intrusion detection evaluation in 1999. Three weeks of training and two weeks of test data were generated on a test ...
Richard Lippmann, Joshua W. Haines, David J. Fried...
eXpert-BSM is a real time forward-reasoning expert system that analyzes Sun Solaris audit trails. Based on many years of intrusion detection research, eXpert-BSM's knowledge ...
We describe the goals of the IETF's Intrusion Detection Working Group (IDWG) and the requirements for a transport protocol to communicate among intrusion detection systems. W...
Tim Buchheim, Michael Erlinger, Ben Feinstein, Gre...
Intrusion detection aims at raising an alarm any time the security of an IT system gets compromised. Though highly successful, Intrusion Detection Systems are all susceptible of mi...
Abstract. We consider cooperating intrusion detection agents that limit the cooperation information flow with a focus on privacy and confidentiality. Generalizing our previous work...
Pattern matching for network security and intrusion detection demands exceptionally high performance. Much work has been done in this field, and yet there is still significant roo...
In this paper, we introduce a novel architecture for a hardware based network intrusion detection system (NIDS). Current software-based NIDS are too compute intensive and can not ...