Dual-Layered Approach for Malicious Domain Detection

Nadide Bilge Doǧan, Alp Bariş Beydemir, Serif Bahtiyar, Umutcan Doǧan

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

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 dilİngilizce
Ana bilgisayar yayını başlığıUBMK 2024 - Proceedings
Ana bilgisayar yayını alt yazısı9th International Conference on Computer Science and Engineering
EditörlerEsref Adali
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar725-730
Sayfa sayısı6
ISBN (Elektronik)9798350365887
DOI'lar
Yayın durumuYayınlandı - 2024
Etkinlik9th International Conference on Computer Science and Engineering, UBMK 2024 - Antalya, Turkey
Süre: 26 Eki 202428 Eki 2024

Yayın serisi

AdıUBMK 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
Ülke/BölgeTurkey
ŞehirAntalya
Periyot26/10/2428/10/24

Bibliyografik not

Publisher Copyright:
© 2024 IEEE.

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