LAN Intrusion Detection Using Convolutional Neural Networks

Creative Commons License

Zainel H., KOÇAK C.

APPLIED SCIENCES-BASEL, cilt.12, sa.13, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12 Sayı: 13
  • Basım Tarihi: 2022
  • Doi Numarası: 10.3390/app12136645
  • Dergi Adı: APPLIED SCIENCES-BASEL
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Agricultural & Environmental Science Database, Applied Science & Technology Source, Communication Abstracts, INSPEC, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
  • Anahtar Kelimeler: intrusion, deep learning, convolutional neural network, attack, machine learning
  • Gazi Üniversitesi Adresli: Evet

Özet

The world's reliance the use of the internet is growing constantly, and data are considered the most precious parameter nowadays. It is critical to keep information secure from unauthorized people and organizations. When a network is compromised, information is taken. An intrusion detection system detects both known and unexpected assaults that allow a network to be breached. In this research, we model an intrusion detection system trained to identify such attacks in LANs, and any computer network that uses data. We accomplish this by employing neural networks, a machine learning technique. We also investigate how well our model performs in multiclass categorization scenarios. On the NSL-KDD dataset, we investigate the performance of Convolutional Neural Networks such as CNN and CNN with LSTM. Our findings suggest that utilizing Convolutional Neural Networks to identify network intrusions is an effective strategy.