USE OF ARTIFICIAL INTELLIGENCE FOR PROACTIVE DETECTION OF CYBER THREATS IN CORPORATE ENVIRONMENTS
DOI:
https://doi.org/10.63330/aurumpub.021-005Palabras clave:
Artificial Intelligence, Cybersecurity, Threat detection, Behavioral analysis, Machine learningResumen
This study addresses the use of Artificial Intelligence for proactive detection of cyber threats in corporate environments, presenting the main concepts, technologies, and models that enable understanding how the adoption of intelligent solutions strengthens organizations’ digital security. The objective was to analyze how techniques such as machine learning, deep learning, behavioral analysis, and event correlation contribute to improving attack identification, especially those lacking known signatures or prior evidence, such as zero-day attacks. The research employed a bibliographic and qualitative methodology, based on the analysis of books, scientific articles, and specialized documents that discuss the evolution of digital threats, the fundamentals of information security, and the role of intelligent technologies in protecting corporate infrastructures. The results demonstrated that traditional security systems exhibit significant limitations in the face of increasingly sophisticated attacks, highlighting the need for tools capable of continuous learning and real-time analysis of large data volumes. It was observed that AI-based solutions allow greater accuracy in anomaly detection, reduction of false positives, anticipation of malicious behaviors, and increased efficiency in incident response. The study concludes that the use of Artificial Intelligence in cybersecurity represents a significant advancement for companies, offering more dynamic, adaptable, and effective resources to combat contemporary threats. Furthermore, the adoption of these technologies contributes to building a safer, more predictable, and resilient organizational environment, reinforcing the importance of investing in intelligent protection models as an essential component of security management strategies.
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Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
