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Wykrywanie WlamaŃ Przy UŻyciu Selekcji Cech I Hybrydyzacji

Wykrywanie WlamaŃ Przy UŻyciu Selekcji Cech I Hybrydyzacji


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About the Book

W dzisiejszych czasach bardzo ważne jest utrzymanie wysokiego poziomu bezpieczeństwa, aby zapewnic bezpieczną i zaufaną komunikację informacji pomiędzy różnymi organizacjami. Bezsprzecznie, szeroki zakres technologii bezpieczeństwa, takich jak szyfrowanie informacji, kontrola dostępu i zapobieganie wlamaniom są wykorzystywane do ochrony systemów opartych na sieci, ale nadal istnieje wiele niewykrytych wlamań.Ten projekt przedstawia przegląd wykrywania wlamań i hybrydowy algorytm klasyfikacji oparty na naiwnej baye i K Nearest neighbour. Zbiór danych jest najpierw przepuszczany przez algorytm naiwnej baye w celu klasyfikacji, generując priorytety i prawdopodobieństwa warunkowe dla każdego przykladu w zbiorze danych. Jeśli wystąpi blędna klasyfikacja, przyklad jest przekazywany do KNN, który następnie szereguje sąsiedztwo przykladu, a wynikowe przyklady są ważone przy użyciu podobieństwa każdego z sąsiadów przykladu, jeśli Sim(X, Dj) jest równe 1, to X jest normalny, w przeciwnym razie algorytm znajduje K największych Sim(X, Dj), sprawdza je względem kryterium zatrzymania (próg).


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Product Details
  • ISBN-13: 9786203335156
  • Publisher: KS Omniscriptum Publishing
  • Publisher Imprint: Wydawnictwo Nasza Wiedza
  • Height: 229 mm
  • No of Pages: 68
  • Spine Width: 4 mm
  • Width: 152 mm
  • ISBN-10: 6203335150
  • Publisher Date: 16 Feb 2021
  • Binding: Paperback
  • Language: Polish
  • Returnable: N
  • Weight: 163 gr


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