In recent years, deep neural networks (DNNs) have witnessed extensive applications, and protecting their intellectual property (IP) is thus crucial. As a non-invasive way for model IP protection, model fingerprinting has become popular. However, existing single-point based fingerprinting methods are highly sensitive to the changes in the decision boundary, and may suffer from the misjudgment of the resemblance of sparse fingerprinting, yielding high false positives of innocent models. In this paper, we propose ADV-TRA, a more robust fingerprinting scheme that utilizes adversarial trajectories to verify the ownership of DNN models. Benefited from the intrinsic progressively adversarial level, the trajectory is capable of tolerating greater degree of alteration in decision boundaries.

Author-title index to volume six of "AI Magazine

It has been a gratifying experience to observe and to One major exception: I know that many members participate in the growth of our Association's Magazine. As the official publication worried about how we'd get enough material to put out the Moreover, there is no articles full, and I was concerned that it just be nonempty! We don't have that I had rejected almost nothing since I had taken over-the editorial staff to do extensive rewriting or editing. "All the news we get we print" was close to the truth. Most of the magazine published four issues, averaging a little over 40 pages each.

See Steamer: an Interactive Inspectable Samulation-Based Reid.

How to Get the Most Out of IJCAI-83 Vol IV, No 1, p 35, Winter-Spring, 1983.