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» LIDS: Learning Intrusion Detection System
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SP
2010
IEEE
187views Security Privacy» more  SP 2010»
13 years 8 months ago
Outside the Closed World: On Using Machine Learning for Network Intrusion Detection
Abstract—In network intrusion detection research, one popular strategy for finding attacks is monitoring a network’s activity for anomalies: deviations from profiles of norma...
Robin Sommer, Vern Paxson
ICNC
2005
Springer
13 years 10 months ago
Applying Genetic Programming to Evolve Learned Rules for Network Anomaly Detection
The DARPA/MIT Lincoln Laboratory off-line intrusion detection evaluation data set is the most widely used public benchmark for testing intrusion detection systems. But the presence...
Chuanhuan Yin, Shengfeng Tian, Houkuan Huang, Jun ...
ICIAP
2005
ACM
14 years 5 months ago
Analyzing TCP Traffic Patterns Using Self Organizing Maps
The continuous evolution of the attacks against computer networks has given renewed strength to research on anomaly based Intrusion Detection Systems, capable of automatically dete...
Stefano Zanero
IJNSEC
2010
141views more  IJNSEC 2010»
12 years 11 months ago
Protection of an Intrusion Detection Engine with Watermarking in Ad Hoc Networks
In this paper we present an intrusion detection engine comprised of two main elements; firstly, a neural network for the actual detection task and secondly watermarking techniques...
Aikaterini Mitrokotsa, Nikos Komninos, Christos Do...
CIS
2005
Springer
13 years 10 months ago
Computational Intelligence for Network Intrusion Detection: Recent Contributions
Computational intelligence has figured prominently in many solutions to the network intrusion detection problem since the 1990s. This prominence and popularity has continued in the...
Asim Karim