Adversarial Attacks | Aleksandar Tomcic | DSC Europe 23
In his talk, he explored adversarial attacks, which are techniques employed in the field of Machine Learning with the intention to deceive models through malicious inputs. These attacks serve various purposes, with one of the most common being an attempt to disrupt or "breakdown" standard models of Deep Neural Networks. He discussed the ongoing efforts in addressing these attacks, acknowledging that a definitive solution has not been found yet. The talk highlighted the vulnerability of DNNs, emphasizing the need for continued research to develop effective countermeasures.
This speech by Aleksandar Tomcic was held on November 22nd at Data Science Conference Europe 2023 in Belgrade.
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