METHODS FOR DETECTING GRAPHIC FORGERIES IN THE DIGITAL ENVIRONMENT

The article is devoted to the problem of detecting graphic forgeries in the digital environment, specifically within phishing attacks. It examines sophisticated techniques used to disguise fraudulent websites as legitimate online banking services and governmental platforms, such as interface cloning, typosquatting, and homograph attacks. The study highlights that over 90% of phishing sites now use valid TLS certificates to create a false sense of security. Phishing indicators are systematized, and a comprehensive algorithm for domain verification is proposed. This approach combines user visual literacy with instrumental methods like Whois analysis and threat intelligence services, enabling users to timely recognize threats and prevent the loss of confidential data.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-12
DOI
https://doi.org/10.5281/zenodo.17939513
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

METHODS FOR DETECTING GRAPHIC FORGERIES IN THE DIGITAL ENVIRONMENT

Zenodo (CERN European Organization for Nuclear Research)
Spam and Phishing Detection
article

METHODS FOR DETECTING GRAPHIC FORGERIES IN THE DIGITAL ENVIRONMENT

article en

Abstract

The article is devoted to the problem of detecting graphic forgeries in the digital environment, specifically within phishing attacks. It examines sophisticated techniques used to disguise fraudulent websites as legitimate online banking services and governmental platforms, such as interface cloning, typosquatting, and homograph attacks. The study highlights that over 90% of phishing sites now use valid TLS certificates to create a false sense of security. Phishing indicators are systematized, and a comprehensive algorithm for domain verification is proposed. This approach combines user visual literacy with instrumental methods like Whois analysis and threat intelligence services, enabling users to timely recognize threats and prevent the loss of confidential data.

Zenodo (CERN European Organization for Nuclear Research)
Kherson State University (UA)
Quality Education
Openalex Percentile: Top 26%
Spam and Phishing Detection
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