March 2024
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Guarding the Future: Navigating the Maze of Adversarial AI Attacks Adversarial machine learning (AML) attacks pose a significant risk to AI systems, which are becoming increasingly integral to both our businesses and daily lives. These attacks can degrade AI performance, produce incorrect results, lead to data breaches, and cause various security problems. Understanding the nature…
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Shifting Gears: Machine Learning’s New Frontier in Cybersecurity In the realm of cybersecurity, machine learning (ML) has predominantly been wielded as a tool for detection. Traditionally focused on identifying threats through algorithms that parse vast datasets for anomalies, ML has been the backbone of cybersecurity operations in enterprises. However, the evolving complexity of cyber threats…
