| DC Field | Value | Language |
| dc.contributor.author | Sudani, Н. Н. | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2026-04-28T06:14:05Z | - |
| dc.date.available | 2026-04-28T06:14:05Z | - |
| dc.date.issued | 2026 | - |
| dc.identifier.citation | Sudani, Н. Н. Enhancing cybersecurity resilience through an integrated artificial intelligence framework / H. H. Sudani // Технические средства защиты информации : материалы ХXIV Международной научно-технической конференции, Минск, 8 апреля 2026 года / Белорусский государственный университет информатики и радиоэлектроники [и др.] ; редкол.: О. В. Бойправ [и др.]. – Минск, 2026. – С. 105–109. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/63432 | - |
| dc.description.abstract | As cyber threats become increasingly complex, artificial intelligence (Al) has become a critical tool for strengthening cybersecurity systems. This article examines how Al improves the effectiveness of cyber defense through real-time threat detection, behavioral analysis, and automated response mechanisms. However, the integration of Al also creates new vulnerabilities, including adversarial attacks, data dependency risks, and ethical concerns related to surveillance and privacy. The dual nature of Al - as a powerful defense mechanism and a potential security risk-underscores the need for responsible implementation. The paper concludes by emphasizing the importance of transparency, robust data governance, and continuous model evaluation in building resilient АІ-powered cybersecurity frameworks. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | БГУИР | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | artificial intelligence | en_US |
| dc.subject | cybersecurity | en_US |
| dc.subject | adversarial attacks | en_US |
| dc.subject | data privacy | en_US |
| dc.subject | security automation | en_US |
| dc.title | Enhancing cybersecurity resilience through an integrated artificial intelligence framework | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | ТСЗИ 2026
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