Spotting the Hook: Leveraging Domain Data for Advanced Phishing Detection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F24%3APU154679" target="_blank" >RIV/00216305:26230/24:PU154679 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/document/10814617" target="_blank" >https://ieeexplore.ieee.org/document/10814617</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.23919/CNSM62983.2024.10814617" target="_blank" >10.23919/CNSM62983.2024.10814617</a>

Result language

angličtina

Original language name

Spotting the Hook: Leveraging Domain Data for Advanced Phishing Detection

Original language description

Phishing is a major threat, using deceptive tactics to steal sensitive information like passwords and financial details. The rapid innovation by cybercriminals and sophisticated social engineering amplify the challenges in combating phishing campaigns. Traditional blocklisting methods struggle due to the dynamic nature of the Internet and the continuous emergence of new phishing sites. Our research presents an innovative approach to detect phishing domains using machine learning classifiers built upon an extensive array of information combined from DNS records, IP addresses, RDAP servers, TLS certificates, and geolocation data for over 500,000 Internet domains. Using a fine-tailored vector of 143 unique features and seven classification methods, we have achieved a 0.9830 precision rate, an F1 score of 0.9770, and a remarkably low false positive rate of only 0.27%. We further examines the contribution of individual features and the overall impact of information from the utilized data sources on the decision making of the classifiers.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/VJ02010024" target="_blank" >VJ02010024: Flow-based Encrypted Traffic Analysis</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2024 10th International Conference on Network and Service Management (CNSM)

ISBN

978-3-903176-66-9

ISSN

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e-ISSN

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Number of pages

7

Pages from-to

1-7

Publisher name

Institute of Electrical and Electronics Engineers

Place of publication

Praha

Event location

Praha

Event date

Oct 28, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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