A Hybrid Method for Intrusion Detection

Canbay Y., SAĞIROĞLU Ş.

IEEE 14th International Conference on Machine Learning and Applications ICMLA, Florida, Amerika Birleşik Devletleri, 9 - 11 Aralık 2015, ss.156-161 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/icmla.2015.197
  • Basıldığı Şehir: Florida
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.156-161
  • Anahtar Kelimeler: Intrusion detection, k-nearest neighbor, genetic algorithm, network attacks, FEATURE-SELECTION
  • Gazi Üniversitesi Adresli: Evet

Özet

Intrusion Detection Systems (IDSs) are used to detect malicious actions on information systems such as computing and networking systems. Abnormal behaviors or activities on the network systems could be detected by security systems. But, conventional security systems such as anti-virus and firewall cannot be successful in many malicious actions. To overcome this problem, better and more intelligent IDS solutions are required.