Özet
The Domain Name System (DNS) plays a critical role in network security, yet faces numerous attacks, particularly from malicious domains. In this research, we propose a novel method to reduce the attacks by combining a mixture of expert structure with DistilBERT and feature extraction from various data sources, including WHOIS API, IP Geolocation API, DNS Lookup API, and SSL Certificate Control API, to classify domain security status. Utilizing a double-layer structure, we initially classify URLs as benign, phishing, malware, or defacement categories using a mixture of experts. Subsequently, URLs were flagged with feature extraction methods for further categorization. This approach provides a robust classification accuracy that offers a comprehensive solution for detecting malicious domains.
Orijinal dil | İngilizce |
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Ana bilgisayar yayını başlığı | UBMK 2024 - Proceedings |
Ana bilgisayar yayını alt yazısı | 9th International Conference on Computer Science and Engineering |
Editörler | Esref Adali |
Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
Sayfalar | 725-730 |
Sayfa sayısı | 6 |
ISBN (Elektronik) | 9798350365887 |
DOI'lar | |
Yayın durumu | Yayınlandı - 2024 |
Etkinlik | 9th International Conference on Computer Science and Engineering, UBMK 2024 - Antalya, Turkey Süre: 26 Eki 2024 → 28 Eki 2024 |
Yayın serisi
Adı | UBMK 2024 - Proceedings: 9th International Conference on Computer Science and Engineering |
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???event.eventtypes.event.conference??? | 9th International Conference on Computer Science and Engineering, UBMK 2024 |
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Ülke/Bölge | Turkey |
Şehir | Antalya |
Periyot | 26/10/24 → 28/10/24 |
Bibliyografik not
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