PHISHING ATTACKS ON ENCRYPTED MESSENGERS: METHODS, RISKS AND PROTECTION RECOMMENDATIONS (USING THE EXAMPLE OF SIGNAL MESSENGER)

This article analyzes phishing attack methods that pose a serious threat to encrypted mobile messengers, particularly Signal. Special attention is given to the latest techniques used by Russian hackers associated with the GRU RF, involving fake QR codes. It is demonstrated how attackers can unauthorizedly link additional devices to user accounts, enabling real-time communication tracking. The effectiveness of various security measures is examined, including Signal’s security updates, two-factor authentication, comprehensive operating system protection, and tools such as Google Play Protect. The presented findings highlight the necessity of increased vigilance regarding QR code verification and regular monitoring of linked devices. The practical recommendations provided in this study aim to reduce the risk of account compromise, protect confidential information, and enhance users’ overall cybersecurity levels. Additionally, the article explores potential improvements to messenger security systems, which may be beneficial for developers, government agencies, and cybersecurity professionals. Furthermore, challenges associated with integrating advanced security technologies are discussed, as well as the adaptation of traditional approaches to modern cyber threats. Thus, this research makes a significant contribution to developing modern methodologies for countering phishing attacks, identifying future directions for the design and implementation of protective technologies for mobile platforms, ensuring a higher level of privacy and security in the digital environment.

Authors

Publication Details

Journal
Cybersecurity Education Science Technique
Published
2025-01-01
DOI
https://doi.org/10.28925/2663-4023.2025.27.734
Citations
1
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
3.25
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article

PHISHING ATTACKS ON ENCRYPTED MESSENGERS: METHODS, RISKS AND PROTECTION RECOMMENDATIONS (USING THE EXAMPLE OF SIGNAL MESSENGER)

Volodymyr Zvieriev, Dmytro Prokopovych-Tkachenko, Valerii Bushkov, Borys Khrushkov
1 citations
Cybersecurity Education Science Technique
Spam and Phishing Detection
3.25
article

PHISHING ATTACKS ON ENCRYPTED MESSENGERS: METHODS, RISKS AND PROTECTION RECOMMENDATIONS (USING THE EXAMPLE OF SIGNAL MESSENGER)

Volodymyr Zvieriev, Dmytro Prokopovych-Tkachenko, Valerii Bushkov, Borys Khrushkov
article en
1 citations

Abstract

This article analyzes phishing attack methods that pose a serious threat to encrypted mobile messengers, particularly Signal. Special attention is given to the latest techniques used by Russian hackers associated with the GRU RF, involving fake QR codes. It is demonstrated how attackers can unauthorizedly link additional devices to user accounts, enabling real-time communication tracking. The effectiveness of various security measures is examined, including Signal’s security updates, two-factor authentication, comprehensive operating system protection, and tools such as Google Play Protect. The presented findings highlight the necessity of increased vigilance regarding QR code verification and regular monitoring of linked devices. The practical recommendations provided in this study aim to reduce the risk of account compromise, protect confidential information, and enhance users’ overall cybersecurity levels. Additionally, the article explores potential improvements to messenger security systems, which may be beneficial for developers, government agencies, and cybersecurity professionals. Furthermore, challenges associated with integrating advanced security technologies are discussed, as well as the adaptation of traditional approaches to modern cyber threats. Thus, this research makes a significant contribution to developing modern methodologies for countering phishing attacks, identifying future directions for the design and implementation of protective technologies for mobile platforms, ensuring a higher level of privacy and security in the digital environment.

Cybersecurity Education Science TechniqueVol. 3(27)
Openalex Percentile: Top 10%
Spam and Phishing Detection
3.25
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