Intruder Data Classification Using GM-SOM - Computer Information Systems and Industrial Management Access content directly
Conference Papers Year : 2012

Intruder Data Classification Using GM-SOM

Petr Gajdoš
  • Function : Author
  • PersonId : 1011361
Pavel Moravec
  • Function : Author
  • PersonId : 1009858


This paper uses a simple modification of classic Kohonen network (SOM), which allows parallel processing of input data vectors or partitioning the problem in case of insufficient resources (memory, disc space, etc.) to process all input vectors at once. The algorithm has been implemented to meet a specification of modern multicore graphics processors to achieve massive parallelism. The algorithm pre-selects potential centroids of data clusters and uses them as weight vectors in the final SOM network.In this paper, the algorithm is used on a well-known KDD Cup 1999 intruders dataset.
Fichier principal
Vignette du fichier
978-3-642-33260-9_7_Chapter.pdf (5.57 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01551714 , version 1 (30-06-2017)





Petr Gajdoš, Pavel Moravec. Intruder Data Classification Using GM-SOM. 11th International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2012, Venice, Italy. pp.92-100, ⟨10.1007/978-3-642-33260-9_7⟩. ⟨hal-01551714⟩
44 View
59 Download



Gmail Facebook X LinkedIn More