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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2510.14198 |
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| _version_ | 1866918161655267328 |
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| author | Munny, Morium Akter Alam, Mahbub Paul, Sonjoy Kumar Timko, Daniel Rahman, Muhammad Lutfor Saxena, Nitesh |
| author_facet | Munny, Morium Akter Alam, Mahbub Paul, Sonjoy Kumar Timko, Daniel Rahman, Muhammad Lutfor Saxena, Nitesh |
| contents | Toll scams involve criminals registering fake domains that pretend to be legitimate transportation agencies to trick users into making fraudulent payments. Although these scams are rapidly increasing and causing significant harm, they have not been extensively studied. We present the first large-scale analysis of toll scam domains, using a newly created dataset of 67,907 confirmed scam domains mostly registered in 2025. Our study reveals that attackers exploit permissive registrars and less common top-level domains, with 86.9% of domains concentrated in just five non-mainstream TLDs and 72.9% registered via a single provider. We also discover specific registration patterns, including short bursts of activity that suggest automated, coordinated attacks, with over half of domains registered in the first quarter of 2025. This extreme temporal clustering reflects highly synchronized campaign launches. Additionally, we build a simple predictive model using only domain registration data to predict which scam domains are likely to be suspended -- a proxy for confirmed abuse -- achieving 80.4% accuracy, and 92.3% sensitivity. Our analysis reveals attacker strategies for evading detection -- such as exploiting obscure TLDs, permissive registrars, and coordinated registration bursts -- which can inform more targeted interventions by registrars, hosting providers, and security platforms. However, our results suggest that registration metadata alone may be insufficient, and incorporating features from domain URLs and webpage content could further improve detection. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_14198 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Infrastructure Patterns in Toll Scam Domains: A Comprehensive Analysis of Cybercriminal Registration and Hosting Strategies Munny, Morium Akter Alam, Mahbub Paul, Sonjoy Kumar Timko, Daniel Rahman, Muhammad Lutfor Saxena, Nitesh Cryptography and Security Toll scams involve criminals registering fake domains that pretend to be legitimate transportation agencies to trick users into making fraudulent payments. Although these scams are rapidly increasing and causing significant harm, they have not been extensively studied. We present the first large-scale analysis of toll scam domains, using a newly created dataset of 67,907 confirmed scam domains mostly registered in 2025. Our study reveals that attackers exploit permissive registrars and less common top-level domains, with 86.9% of domains concentrated in just five non-mainstream TLDs and 72.9% registered via a single provider. We also discover specific registration patterns, including short bursts of activity that suggest automated, coordinated attacks, with over half of domains registered in the first quarter of 2025. This extreme temporal clustering reflects highly synchronized campaign launches. Additionally, we build a simple predictive model using only domain registration data to predict which scam domains are likely to be suspended -- a proxy for confirmed abuse -- achieving 80.4% accuracy, and 92.3% sensitivity. Our analysis reveals attacker strategies for evading detection -- such as exploiting obscure TLDs, permissive registrars, and coordinated registration bursts -- which can inform more targeted interventions by registrars, hosting providers, and security platforms. However, our results suggest that registration metadata alone may be insufficient, and incorporating features from domain URLs and webpage content could further improve detection. |
| title | Infrastructure Patterns in Toll Scam Domains: A Comprehensive Analysis of Cybercriminal Registration and Hosting Strategies |
| topic | Cryptography and Security |
| url | https://arxiv.org/abs/2510.14198 |