Characterizing and Mitigating Phishing Attacks at ccTLD Scale

Phishing on the web is a model of social engineering and an attack vector for getting access to sensitive and financial data of individuals and corporations. Phishing has been identified as one of the prime cyber threats in recent years. With the goal to effectively identify and mitigate phishing as early as possible, we present in this paper a longitudinal analysis of phishing attacks from the vantage point of three country-code top-level domain (ccTLD) registries that manage more than 8 million active domains – namely the Netherlands’ .nl, Ireland’s .ie, and Belgium’s .be. We perform a longitudinal analysis on phishing attacks spanning up to 10 years, based on more than 28 thousand phishing domains. Our results show two major attack strategies: national companies and organizations are far more often impersonated using malicious registered domains under their country’s own ccTLD, which enables better mimicry of the impersonated company. In stark contrast, international companies are impersonated using any domains that can be compromised, reducing overall mimicry but bearing no registration and financial costs. Although most research works focus on detecting new domain names, we show that 80% of phishing attacks in the studied ccTLDs employ compromised domain names. We find banks, financial institutions, and high-tech giant companies at the top of the most impersonated targets. We also show the impact of ccTLDs’ registration and abuse handling policies on preventing and mitigating phishing attacks, and that mitigation is complex and performed at both web and DNS level at different intermediaries. Last, our results provide a unique opportunity for ccTLDs to compare and revisit their policies and impacts, with the goal of improving mitigation procedures.

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Publication Details

Published
2024-12-02
DOI
https://doi.org/10.1145/3658644.3690192
Citations
6
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
4.67

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article

Characterizing and Mitigating Phishing Attacks at ccTLD Scale

Georgios Smaragdakis, Moritz Müller, Maciej Korczyński, Sebastian Castro et al.
6 citations
Spam and Phishing Detection
4.67
article

Characterizing and Mitigating Phishing Attacks at ccTLD Scale

Georgios Smaragdakis, Moritz Müller, Maciej Korczyński, Sebastian Castro, Giovane C. M. Moura, Thijs van den Hout, M. Bosteels, Thymen Wabeke, Thomas Daniels
article en
6 citations

Abstract

Phishing on the web is a model of social engineering and an attack vector for getting access to sensitive and financial data of individuals and corporations. Phishing has been identified as one of the prime cyber threats in recent years. With the goal to effectively identify and mitigate phishing as early as possible, we present in this paper a longitudinal analysis of phishing attacks from the vantage point of three country-code top-level domain (ccTLD) registries that manage more than 8 million active domains – namely the Netherlands’ .nl, Ireland’s .ie, and Belgium’s .be. We perform a longitudinal analysis on phishing attacks spanning up to 10 years, based on more than 28 thousand phishing domains. Our results show two major attack strategies: national companies and organizations are far more often impersonated using malicious registered domains under their country’s own ccTLD, which enables better mimicry of the impersonated company. In stark contrast, international companies are impersonated using any domains that can be compromised, reducing overall mimicry but bearing no registration and financial costs. Although most research works focus on detecting new domain names, we show that 80% of phishing attacks in the studied ccTLDs employ compromised domain names. We find banks, financial institutions, and high-tech giant companies at the top of the most impersonated targets. We also show the impact of ccTLDs’ registration and abuse handling policies on preventing and mitigating phishing attacks, and that mitigation is complex and performed at both web and DNS level at different intermediaries. Last, our results provide a unique opportunity for ccTLDs to compare and revisit their policies and impacts, with the goal of improving mitigation procedures.

Central Statistics Office (IE), SIDN Fonds (NL), Université Grenoble Alpes (FR), University of Twente (NL), Delft University of Technology (NL), KU Leuven (BE)
Agentschap Innoveren en Ondernemen, European Commission, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 5%
Spam and Phishing Detection
4.67
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