Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models
Industry experts analyze emerging threats surrounding Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models.
Summary
No summary yet — watch the video above, or open it on YouTube.
Related talks
IEEE Symposium on Security and Privacy·15 min
Presenters detail vulnerability discovery and exploitation in REDEEM MYSELF: Purifying Backdoors in Deep Learning Models using Self Attention Distillation.
IEEE Symposium on Security and Privacy·17 min
Engineers explore architecture and security mechanisms for Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering.
IEEE Symposium on Security and Privacy·19 min
Analysts investigate attack surfaces and defenses concerning Hark: A Deep Learning System for Navigating Privacy Feedback at Scale.


