Siber Güvenlikte CIC-Darknet2020 Veri Seti Kullanarak VPN/NoVPN ve Tor/NoTor Sınıflandırması: Basit ve Karmaşık Modellerin Kullanımı
Öz
Anahtar Kelimeler
Kaynakça
- Abu Al-Haija Q, Krichen M, Abu Elhaija W. Machine-learning-based darknet traffic detection system for IoT applications. Electronics 2022; 11: 556.
- Iliadis LA, Kaifas T. Darknet traffic classification using machine learning techniques. In: 2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST). IEEE, 2021, pp. 1–4.
- Lotfollahi M, Jafari Siavoshani M, Shirali Hossein Zade R, et al. Deep packet: A novel approach for encrypted traffic classification using deep learning. Soft Comput 2020; 24: 1999–2012.
- Afuwape AA, Xu Y, Anajemba JH, et al. Performance evaluation of secured network traffic classification using a machine learning approach. Comput Stand Interfaces 2021; 78: 103545.
- Lingyu J, Yang L, Bailing W, et al. A hierarchical classification approach for tor anonymous traffic. In: 2017 IEEE 9th International conference on communication software and networks (ICCSN). IEEE, 2017, pp. 239–243.
- Sarkar D, Vinod P, Yerima SY. Detection of Tor traffic using deep learning. In: 2020 IEEE/ACS 17th International Conference on Computer Systems and Applications (AICCSA). IEEE, 2020, pp. 1–8.
- Rao Z, Niu W, Zhang X, et al. Tor anonymous traffic identification based on gravitational clustering. Peer-to-Peer Netw Appl 2018; 11: 592–601.
- Hu X, Gao Y, Cheng G, et al. An Adversarial Learning-based Tor Malware Traffic Detection Model. In: GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022, pp. 74–79.
Ayrıntılar
Birincil Dil
Türkçe
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yazarlar
Yusuf Alaca
*
0000-0002-4490-5384
Türkiye
Yayımlanma Tarihi
1 Eylül 2023
Gönderilme Tarihi
2 Mayıs 2023
Kabul Tarihi
1 Temmuz 2023
Yayımlandığı Sayı
Yıl 2023 Cilt: 35 Sayı: 2
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