PRODeep: A Platform for Robustness Verification of Deep Neural Networks

Paper Synopsis

PRODeep is a platform for robustness verification of deep neural networks (DNNs). It incorporates constraint-based, abstraction-based, and optimization-based robustness verification algorithms. It has a modular architecture, enabling easy comparison of different algorithms. Significantly, PRODeep provides a user-friendly GUI, visualizing both inputs and outputs and providing an intuitive way to analyze the robustness properties. It is easy to get started with, so you can easily design some experiments to evaluate the robustness properties of your DNNs.

Cite the Paper

Renjue Li, Jianlin Li, Cheng-Chao Huang, Pengfei Yang, Xiaowei Huang, Lijun Zhang, Bai Xue, Holger Hermanns: PRODeep: a platform for robustness verification of deep neural networks. In ESEC/FSE’20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Virtual Event, USA, November 8-13, 2020, pages 1630-1634, 2020. DOI BIB

Video Presentation

Video presentation, in English