USING AI TO PREVENT EMAIL PHISHING ATTACKS

This article examines the current problems and the devastating effects of phishing email attacks. The importance of preventive measures to protect organizations from data leakage and potential catastrophic consequences is emphasized. The main types of phishing attacks and the need to implement solutions based on artificial intelligence (AI) to effectively reduce risks are described. The work used methods for recognizing early signs of phishing using artificial intelligence and machine learning. Python and Google Colab were used for development, which made it possible to effectively analyze data and train models. Special attention was paid to the development of unique methods and the use of modern software. As a result of the study, data were obtained confirming the high effectiveness of AI tools in recognizing phishing attacks. Artificial intelligence technologies have significantly improved the accuracy of phishing detection and supported adaptation to new cyber threats. The analysis shows that the use of AI allows not only to detect attacks in a timely manner, but also to develop prevention strategies. The practical significance of the results lies in the possibility of integrating the developed methods into existing security systems. The work offers a strategic approach combining technological advances and organizational practices to create sustainable information security.

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Publication Details

Journal
Bulletin of Shakarim University Technical Sciences
Published
2024-12-27
DOI
https://doi.org/10.53360/2788-7995-2024-4(16)-8
Primary Topic
Spam and Phishing Detection
Type
article
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article

USING AI TO PREVENT EMAIL PHISHING ATTACKS

Bayan Abduraimova, A. B. Kakenova, S. A. Santeeva
Bulletin of Shakarim University Technical Sciences
Spam and Phishing Detection
article

USING AI TO PREVENT EMAIL PHISHING ATTACKS

Bayan Abduraimova, A. B. Kakenova, S. A. Santeeva
article en

Abstract

This article examines the current problems and the devastating effects of phishing email attacks. The importance of preventive measures to protect organizations from data leakage and potential catastrophic consequences is emphasized. The main types of phishing attacks and the need to implement solutions based on artificial intelligence (AI) to effectively reduce risks are described. The work used methods for recognizing early signs of phishing using artificial intelligence and machine learning. Python and Google Colab were used for development, which made it possible to effectively analyze data and train models. Special attention was paid to the development of unique methods and the use of modern software. As a result of the study, data were obtained confirming the high effectiveness of AI tools in recognizing phishing attacks. Artificial intelligence technologies have significantly improved the accuracy of phishing detection and supported adaptation to new cyber threats. The analysis shows that the use of AI allows not only to detect attacks in a timely manner, but also to develop prevention strategies. The practical significance of the results lies in the possibility of integrating the developed methods into existing security systems. The work offers a strategic approach combining technological advances and organizational practices to create sustainable information security.

Bulletin of Shakarim University Technical SciencesVol. 1(4(16))
L. N. Gumilyov Eurasian National University (KZ)
Openalex Percentile: Top 57%
Spam and Phishing Detection
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USING AI TO PREVENT EMAIL PHISHING ATTACKS — Bayan Abduraimova, A. B. Kakenova, et al. · Bulletin of Shakarim University Technical Sciences (2024) | TGRS Research Map | TGRS