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РецензированоEN2025

ENSURING CYBERSECURITY WITH ARTIFICIAL INTELLIGENCE

Kalilaev Dauletiyar Bakhtiyarovich (AN D INNOVATION IF = 5.28 1 www.in-academy.uz) · Teacher of TUIT (AN D INNOVATION IF = 5.28 1 www.in-academy.uz) · KEY WORDS (AN D INNOVATION IF = 5.28 1 www.in-academy.uz) · Artificial Intelligence (AI) (AN D INNOVATION IF = 5.28 1 www.in-academy.uz) · Machine Learning (AN D INNOVATION IF = 5.28 1 www.in-academy.uz) · Deep Learning (DL) (AN D INNOVATION IF = 5.28 1 www.in-academy.uz) · Language Processing (NLP) (AN D INNOVATION IF = 5.28 1 www.in-academy.uz) · Anomaly Detection (AN D INNOVATION IF = 5.28 1 www.in-academy.uz) · Automated Response (AN D INNOVATION IF = 5.28 1 www.in-academy.uz) · Threat Intelligence (AN D INNOVATION IF = 5.28 1 www.in-academy.uz)

Центральноазиатский журнал образования и инноваций · 4 · 2025

Аннотация

The relentless evolution of cyber threats, from ransomware to advanced persistent threats (APTs), has exposed the limitations of traditional cybersecurity approaches. Artificial Intelligence (AI) has emerged as a cornerstone technology, offering sophisticated tools for threat detection, predictive analytics, automated response, and threat intelligence. By leveraging machine learning, deep learning, and natural language processing, AI enables adaptive and scalable defenses against increasingly complex attacks. This article provides an in-depth exploration of AI’s transformative role in cybersecurity, detailing its applications, addressing challenges such as adversarial attacks, data biases, and ethical concerns, and envisioning future advancements. Through a comprehensive analysis, it underscores AI’s potential to fortify digital ecosystems while highlighting the need for robust strategies to mitigate its limitations.

Доказательный фрагмент

«The relentless evolution of cyber threats, from ransomware to advanced persistent threats (APTs), has exposed the limitations of traditional cybersecurity approaches.»

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Демо-превью

The relentless evolution of cyber threats, from ransomware to advanced persistent threats (APTs), has exposed the limitations of traditional cybersecurity approaches. Полный текст публикации CiteX не хранит — доступ к первоисточнику открывается по DOI согласно лицензии издателя и выбранному плану.

doi.org/10.5281/zenodo.15348005
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approaches. Artificial Intelligence (AI) has emerged as, Reinforcement Learning (RL), Zero-Day Exploits, Predictive Analytics, Blockchain Integration, Anomaly Detection, Deep Learning (DL), Federated Learning, Quantum Machine Learning, Automation, Automated Response, Data Quality, Advanced Persistent Threats (APTs), and Response (SOAR), Natural Language Processing (NLP), Machine Learning (ML), Security Orchestration, Artificial Intelligence (AI), Adversarial Attacks, Cybersecurity, Ethical Concerns, Privacy, Threat Intelligence
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