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ICIAP
2005
ACM
14 years 9 months ago
Learning Intrusion Detection: Supervised or Unsupervised?
Abstract. Application and development of specialized machine learning techniques is gaining increasing attention in the intrusion detection community. A variety of learning techniq...
Pavel Laskov, Patrick Düssel, Christin Sch&au...
CCGRID
2009
IEEE
14 years 3 months ago
Multi-scale Real-Time Grid Monitoring with Job Stream Mining
—The ever increasing scale and complexity of large computational systems ask for sophisticated management tools, paving the way toward Autonomic Computing. A first step toward A...
Xiangliang Zhang, Michèle Sebag, Céc...
ISMIS
2009
Springer
14 years 3 months ago
Novelty Detection from Evolving Complex Data Streams with Time Windows
Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...
Michelangelo Ceci, Annalisa Appice, Corrado Loglis...
MLDM
2009
Springer
14 years 3 months ago
Relational Frequent Patterns Mining for Novelty Detection from Data Streams
We face the problem of novelty detection from stream data, that is, the identification of new or unknown situations in an ordered sequence of objects which arrive on-line, at cons...
Michelangelo Ceci, Annalisa Appice, Corrado Loglis...
DEXAW
2008
IEEE
121views Database» more  DEXAW 2008»
14 years 3 months ago
Experiences on Designing an Integral Intrusion Detection System
Network Intrusion Detection Systems (NIDS) have the challenge to prevent network attacks and unauthorised remote use of computers. In order to achieve this goal, NIDS usually foll...
Yoseba K. Penya, Pablo Garcia Bringas