Lattice-Quantization Identity Watermarking for Deep Neural Network Ownership Protection
This work proposes a novel lattice quantization-based backdoor watermarking framework for DNNs in black-box settings that embeds the owner’s identity into trigger samples via lattice quantization index modulation, achieving identity encoding while maintaining trigger imperceptibility.