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Інструменти штучного інтелекту для автоматизації тестування на проникнення

Year: 2024

Type: article

Abstract: The article discusses automated penetration testing using artificial intelligence (AI), which significantly enhances the efficiency and accuracy of cybersecurity assessments. AI-based technologies are capable of automating many processes that were previously performed manually, including vulnerability scanning, threat analysis, and exploitation of system weaknesses. Special attention is given to AI-based tools such as DeepExploit, Sn1per, and Cortex XSOAR, which demonstrate substantial advantages over traditional penetration testing methods. The article also addresses the main challenges of implementing AI in penetration testing, including the difficulties of training models and the issue of false positives. The future trends in the use of AI for cybersecurity, such as autonomous testing systems and integration with quantum computing, are explored as well.

Source: Scientific periodicals of Ukraine

Authors: Колощук, Марія Сергіївна, Дячук, Ольга Юріївна, Окунькова, Оксана Олексіївна, Пірог, Олександр Вікторович

Institution: Zhytomyr Polytechnic State University

Language: English

Topic: Web Application Security Vulnerabilities

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W6988455332

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