USE OF ARTIFICIAL INTELLIGENCE IN CYBERSECURITY: POSSIBILITIES OF PREDICTING RISKS
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Keywords: Artificial Intelligence (AI), machine learning (ML), deep learning (DL), phishing emails , ransomware attacks , data quality.##article.abstract##
Abstract: The proliferation of cyber threats in the digital age has made cybersecurity a critical concern for organizations worldwide. As cyberattacks grow in sophistication, traditional security measures struggle to keep pace with the volume and complexity of threats. Artificial Intelligence (AI) has emerged as a transformative technology in cybersecurity, particularly in predicting risks before they materialize into breaches. AI-driven solutions leverage machine learning (ML), deep learning (DL), and other advanced algorithms to analyze vast datasets, detect anomalies, and forecast potential vulnerabilities. This article explores the possibilities of using AI to predict cybersecurity risks, addresses associated challenges, proposes solutions, and provides mathematical formulations and algorithms to support these methods. AI’s predictive capabilities enable organizations to proactively mitigate risks by identifying patterns in network traffic, user behavior, and system vulnerabilities. From detecting phishing emails to anticipating ransomware attacks, AI enhances the speed and accuracy of threat detection, reducing the mean time to respond. However, challenges such as adversarial attacks, data quality, and ethical considerations must be addressed to ensure effective implementation. This article provides a comprehensive analysis of AI’s role in risk prediction, supported by practical solutions, case studies, and algorithmic frameworks.
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