Generative AI revolution in cybersecurity: a comprehensive review of threat intelligence and operations
<p dir="ltr">Cyber threats are increasingly frequent in today’s world, posing challenges for organizations and individuals to protect their data from cybercriminals. On the other hand, Generative Artificial Intelligence (GAI) technology offers an efficient way to automatically addres...
محفوظ في:
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| مؤلفون آخرون: | , , , , , , |
| منشور في: |
2025
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إضافة وسم
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| الملخص: | <p dir="ltr">Cyber threats are increasingly frequent in today’s world, posing challenges for organizations and individuals to protect their data from cybercriminals. On the other hand, Generative Artificial Intelligence (GAI) technology offers an efficient way to automatically address these issues with the help of AI models and algorithms. It can work on more critical security aspects where human intervention is required and handle everyday threat situations autonomously. This research paper explores GAI in enhancing cybersecurity by leveraging AI Models and algorithms. GAI can autonomously address common security issues, detect novel threats, and augment human intervention in critical security aspects. Moreover, this research study also highlights autonomous security enhancements, improved security posture against emerging threats, anomaly detection, and threat response. Besides this, we have discussed the GAI limitations, such as occasional incorrect results, expensive training, and the potential for misuse by malicious actors for illegal activities. This research study also provides valuable insights into the balanced adoption of GAI in cybersecurity, ensuring effective threat migration without compromising system integrity.</p><h2>Other Information</h2><p dir="ltr">Published in: Artificial Intelligence Review<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s10462-025-11219-5" target="_blank">https://dx.doi.org/10.1007/s10462-025-11219-5</a></p> |
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