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pro vyhledávání: '"Kiourti, Panagiota"'
Autor:
Kiourti, Panagiota
The growing interest in deploying deep learning models in critical applications has raised concerns about their vulnerabilities, particularly to backdoor or Trojan attacks. These attacks aim to train a network to respond maliciously to specially craf
Externí odkaz:
https://hdl.handle.net/2144/49247
We present a novel methodology for neural network backdoor attacks. Unlike existing training-time attacks where the Trojaned network would respond to the Trojan trigger after training, our approach inserts a Trojan that will remain dormant until it i
Externí odkaz:
http://arxiv.org/abs/2211.01808
Recent studies have shown that neural networks are vulnerable to Trojan attacks, where a network is trained to respond to specially crafted trigger patterns in the inputs in specific and potentially malicious ways. This paper proposes MISA, a new onl
Externí odkaz:
http://arxiv.org/abs/2103.15918
Recent work has identified that classification models implemented as neural networks are vulnerable to data-poisoning and Trojan attacks at training time. In this work, we show that these training-time vulnerabilities extend to deep reinforcement lea
Externí odkaz:
http://arxiv.org/abs/1903.06638