A Compressive Study on Detection Accuracy Model for DoS Attack in SDN Using Ensemble Learning Techniques
Yazarlar (6)
Sindhu Pusarla
Gıtam University, Hindistan
Gıtam University, Hindistan
Umashankar Ghugar
Op Jindal University, Hindistan
Op Jindal University, Hindistan
Prof. Dr. Turgut ÖZSEVEN Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Bhupesh Kumar Dewangan
Op Jindal University, Hindistan
Op Jindal University, Hindistan
Tanupriya Choudhury
Symbiosis Institute Of Technology, Hindistan
Symbiosis Institute Of Technology, Hindistan
Jagdish Chandra Patni
Symbiosis International (Deemed University), Hindistan
Symbiosis International (Deemed University), Hindistan
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| DOI Numarası | 10.1109/ISAS60782.2023.10391345 | ||
| Kongre Adı | 7th International Symposium on Innovative Approaches in Smart Technologies | ||
| Kongre Tarihi | 23-11-2023 / | ||
| Basıldığı Ülke | Türkiye | Basıldığı Şehir | İstanbul |
| Bildiri Linki | - | ||
| UAK Araştırma Alanları |
Makine Öğrenmesi
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| Özet |
| The possible networking architecture known as a “Software-defined Network” (SDN) separates the information and management layers and offers polarized control over the network. This new approach considers responsibilities and empowers network administrators to electronically assign, manage, adjust, and monitor clan behaviour. One important advantage of SDN is its polarising power, which may occasionally cause a serious breach. The snitcher will have access to the complete framework if he is successful in getting to the controller’s core. The regulators are utterly powerless to combat Distributed Denial of Service (DDoS) attacks, which wear down the model and make the administrators of the regulations inaccessible. It’s crucial to identify potential dangers in the controllers early on. As a result, many algorithms and processes. |
| Anahtar Kelimeler |
| DDoS | Logistic Regression | Machine Learning Techniques | Neural | SDN | SVM |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 1 |
| Google Scholar | 2 |