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cs.CR2024
From Attack to Defense: Insights into Deep Learning Security Measures in Black-Box Settings
Firuz Juraev, Mohammed Abuhamad, Eric Chan-Tin +2
Deep Learning (DL) is rapidly maturing to the point that it can be used in safety- and security-crucial applications. However, adversarial samples, which are undetectable to the hu…
cs.CV2024
Impact of Architectural Modifications on Deep Learning Adversarial Robustness
Firuz Juraev, Mohammed Abuhamad, Simon S. Woo +2
Rapid advancements of deep learning are accelerating adoption in a wide variety of applications, including safety-critical applications such as self-driving vehicles, drones, robot…