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» Mining intrusion detection alarms for actionable knowledge
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KDD
2002
ACM
157views Data Mining» more  KDD 2002»
14 years 7 months ago
Learning nonstationary models of normal network traffic for detecting novel attacks
Traditional intrusion detection systems (IDS) detect attacks by comparing current behavior to signatures of known attacks. One main drawback is the inability of detecting new atta...
Matthew V. Mahoney, Philip K. Chan
ICCS
2007
Springer
14 years 1 months ago
Learning Common Outcomes of Communicative Actions Represented by Labeled Graphs
We build a generic methodology based on learning and reasoning to detect specific attitudes of human agents and patterns of their interactions. Human attitudes are determined in te...
Boris Galitsky, Boris Kovalerchuk, Sergei O. Kuzne...
ECAI
2008
Springer
13 years 9 months ago
Intelligent adaptive monitoring for cardiac surveillance
Monitoring patients in intensive care units is a critical task. Simple condition detection is generally insufficient to diagnose a patient and may generate many false alarms to the...
Lucie Callens, Guy Carrault, Marie-Odile Cordier, ...
ICEIS
2008
IEEE
14 years 1 months ago
Next-Generation Misuse and Anomaly Prevention System
Abstract. Network Intrusion Detection Systems (NIDS) aim at preventing network attacks and unauthorised remote use of computers. More accurately, depending on the kind of attack it...
Pablo Garcia Bringas, Yoseba K. Penya
INFOCOM
2005
IEEE
14 years 1 months ago
Bayesian packet loss detection for TCP
— One of TCP’s critical tasks is to determine which packets are lost in the network, as a basis for control actions (flow control and packet retransmission). Modern TCP implem...
Nahur Fonseca, Mark Crovella