Older and Wiser: The Marriage of Device Aging and Intellectual Property Protection of Deep Neural Networks

arXiv:2406.14863v1 Announce Type: new
Abstract: Deep neural networks (DNNs), such as the widely-used GPT-3 with billions of parameters, are often kept secret due to high training costs and privacy concerns surrounding the data used to train them. Previous approaches to securing DNNs typically require expensive circuit redesign, resulting in additional overheads such as increased area, energy consumption, and latency. To address these issues, we propose a novel hardware-software co-design approach for DNN intellectual property (IP) protection that capitalizes on the …

aging arxiv cs.ar cs.cr data device gpt gpt-3 high intellectual property marriage networks neural networks privacy privacy concerns property protection secret securing train training