Data Quality Problem in Al-Based Network Intrusion Detection Systems Studies and a Solution Proposal

Halisdemir M. E., KARACAN H., Pihelgas M., Lepik T., Cho S.

14th International Conference on Cyber Conflict (CyCon) - Keep Moving, Tallinn, Estonya, 31 Mayıs - 03 Haziran 2022, ss.367-383 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Basıldığı Şehir: Tallinn
  • Basıldığı Ülke: Estonya
  • Sayfa Sayıları: ss.367-383
  • Anahtar Kelimeler: intrusion detection systems, datasets, artificial intelligence, Locked Shields
  • Gazi Üniversitesi Adresli: Evet

Özet

Network Intrusion Detection Systems (IDSs) have been used to increase the level of network security for many years. The main purpose of such systems is to detect and block malicious activity in the network traffic. Researchers have been improving the performance of IDS technology for decades by applying various machine-learning techniques. From the perspective of academia, obtaining a quality dataset (i.e. a sufficient amount of captured network packets that contain both malicious and normal traffic) to support machine learning approaches has always been a challenge. There are many datasets publicly available for research purposes, including NSL-KDD, KDDCUP 99, CICIDS 2017 and UNSWNB15.