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» Principled Sampling for Anomaly Detection
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GECCO
2003
Springer
103views Optimization» more  GECCO 2003»
14 years 1 months ago
MILA - Multilevel Immune Learning Algorithm
The biological immune system is an intricate network of specialized tissues, organs, cells, and chemical molecules. T-cell-dependent humoral immune response is one of the complex i...
Dipankar Dasgupta, Senhua Yu, Nivedita Sumi Majumd...
IMC
2006
ACM
14 years 2 months ago
Shared-state sampling
We present an algorithm, Shared-State Sampling (S3 ), for the problem of detecting large flows in high-speed networks. While devised with different principles in mind, S3 turns ...
Frederic Raspall, Sebastià Sallent, Josep Y...
AAAI
2012
11 years 11 months ago
Learning Behavior Models for Hybrid Timed Systems
A tailored model of a system is the prerequisite for various analysis tasks, such as anomaly detection, fault identification, or quality assurance. This paper deals with the algo...
Oliver Niggemann, Benno Stein, Asmir Vodencarevic,...
RAID
2005
Springer
14 years 2 months ago
Anomalous Payload-Based Worm Detection and Signature Generation
New features of the PAYL anomalous payload detection sensor are demonstrated to accurately detect and generate signatures for zero-day worms. Experimental evidence demonstrates tha...
Ke Wang, Gabriela F. Cretu, Salvatore J. Stolfo
CONEXT
2006
ACM
14 years 2 months ago
Synergy: blending heterogeneous measurement elements for effective network monitoring
Network traffic matrices are important for various network planning and management operations. Previous work for estimation of traffic matrices is based on either link load record...
Awais Ahmed Awan, Andrew W. Moore