Artificial Intelligence in Cybersecurity: Exploring AI-Powered Threat Detection and Mitigation Strategies

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@article{1708695,
      author = {Aidar Imashev},
      title = {Artificial Intelligence in Cybersecurity: Exploring AI-Powered Threat Detection and Mitigation Strategies},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {8},
      number = {11},
      pages = {1387-1397},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1708695.pdf},
      abstract = {Today's growing number of cyber threats has revealed that traditional cybersecurity approaches have reached their limits. AI and ML are being adopted, as they contribute reliable and flexible capabilities to the fight against cybercrime. This article studies the role of AI and ML in improved threat detection, automatically handling threats, and forecasting risks for cybersecurity. This paper compares how AI-powered systems, such as anomaly-based intrusion detection systems and intelligent reaction methods, benefit from using computers to make decisions compared to conventional approaches based on rules. Besides, it brings attention to the main issues, including attacks directed at AI by cyber criminals, data privacy risks, and some AI algorithms being difficult to explain. The last part of the article discusses possible future research focused on ethical leadership in AI, teamwork among various experts, and reliable, transparent, and responsible cybersecurity solutions. These points are intended to help guide those working on technology and policies to use AI for better cybersecurity.},
      keywords = {Artificial Intelligence, Cybersecurity, Threat Detection, Machine Learning, Automated Mitigation},
      month = {May},
  }