Artificial intelligence (AI) offers transformative potential across industries, yet its vulnerability to adversarial attacks poses significant risks. Adversarial attacks, in which meticulously crafted inputs deceive AI models, can undermine system reliability, safety, and security. This article explores key strategies for mitigating adversarial manipulation and ensuring robust operations in real-world applications.
Understanding the Threat
Adversarial attacks target inherent sensitivities within machine learning models. By subtly altering input data in ways imperceptible to humans, attackers can:
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