Applying the FGSM poisoning attack to a simulated 5G pathloss regression task raises the reported MSE by about a third, and a gradient-boosted classifier detects the poisoned records, but the paper's restoration result is undermined by comparing metrics on different data subsets.
Perturbation analysis of learning algorithms: Generation of adversarial examples from classification to regression,
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Analysis of the vulnerability of machine learning regression models to adversarial attacks using data from 5G wireless networks
Applying the FGSM poisoning attack to a simulated 5G pathloss regression task raises the reported MSE by about a third, and a gradient-boosted classifier detects the poisoned records, but the paper's restoration result is undermined by comparing metrics on different data subsets.