The prospect of AI-powered cybersecurity systems combating insider threats is an intriguing one. However, their reliance on data may indeed create a paradox that makes them vulnerable to sophisticated social engineering attacks.
Social engineering exploits human psychology, often targeting employees' trust and curiosity. Insider threats can be particularly damaging as they involve individuals with authorized access to sensitive information. AI-powered systems, while adept at pattern recognition and anomaly detection, may struggle to identify subtle manipulations by insiders.
For instance, an insider might create a convincing phishing email that appears to come from a trusted colleague or executive, using language and tone that mimics the original sender. The AI-powered system, trained on vast amounts of data, might flag the email as legitimate, unaware of the insider's intentions.
Moreover, AI systems may over-rely on data, potentially leading to "training data poisoning" - a sce...
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