: Attackers can use bi-level optimization to find the exact "poison" samples that mislead systems into selecting the wrong features, which is devastating for wireless distributed learning.
Recent studies highlight that foundational signal processing tasks are surprisingly vulnerable to data poisoning and feature modification: : Attackers can use bi-level optimization to find
In the "greenhouse" of lab development, machine learning (ML) models look unstoppable. But when they hit the "jungle" of real-world deployment, everything changes. For engineers working in , the stakes are particularly high. Whether it’s autonomous driving, wireless sensor networks, or medical imaging, the data isn't just noise—it's a potential target for manipulation. The Hidden Vulnerability: What is Adversarial Robustness? everything changes. For engineers working in