QuestionQ63

VerifiedProactive Threat Detection

A large financial organization has recently seen an increase in sophisticated cyber threats, including zero-day attacks and advanced persistent threats (APTs). The security team is struggling with traditional detection approaches that rely heavily on signature-based detection and manual intervention, delaying threat identification and mitigation. To strengthen its security posture, the Chief Information Security Officer (CISO) is considering AI-driven solutions that can automatically analyze vast datasets, detect anomalies, and adapt to evolving threats in real time. The objective is to deploy a system that can identify suspicious activity without predefined signatures, enabling faster response times and minimal human oversight. Which key AI technology should the organization prioritize to accomplish this?

Explanation

Machine learning can learn normal and malicious behavioral patterns from large datasets and flag anomalies without relying on predefined signatures. This makes it well suited to detecting novel attacks, including zero-day attacks and APT activity, while adapting detection models as threats evolve.

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