Towards Proactive Domain Name Security: An Adaptive System for.ro domains Reputation Analysis

Carmen Ionela Rotună (), Ioan Ștefan Sacală and Adriana Alexandru ()
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Carmen Ionela Rotună: National Institute for Research and Development in Informatics, 011455 Bucharest, Romania
Ioan Ștefan Sacală: Department of Automatic Control and Systems Engineering, University Politehnica of Bucharest, 313 Splaiul Independenţei, 060042 Bucharest, Romania
Adriana Alexandru: National Institute for Research and Development in Informatics, 011455 Bucharest, Romania

Future Internet, 2025, vol. 17, issue 10, 1-27

Abstract: In a digital landscape marked by the exponential growth of cyber threats, the development of automated domain reputation systems is extremely important. Emerging technologies such as artificial intelligence and machine learning now enable proactive and scalable approaches to early identification of malicious or suspicious domains. This paper presents an adaptive domain name reputation system that integrates advanced machine learning to enhance cybersecurity resilience. The proposed framework uses domain data from .ro domain Registry and several other sources (blacklists, whitelists, DNS, SSL certificate), detects anomalies using machine learning techniques, and scores domain security risk levels. A supervised XGBoost model is trained and assessed through five-fold stratified cross-validation and a held-out 80/20 split. On an example dataset of 25,000 domains, the system attains accuracy 0.993 and F1 0.993 and is exposed through a lightweight Flask service that performs asynchronous feature collection for near real-time scoring. The contribution is a blueprint that links list supervision with registry/DNS/TLS features and deployable inference to support proactive domain abuse mitigation in ccTLD environments.

Keywords: domain reputation; cybersecurity; adaptive system; machine learning; threat intelligence; monitoring; ccTLD; DNS; WHOIS; XGBoost (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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