CAD For Assurance: NEOS Toolset and Deep Learning-Based Model Building Attacks on Arbiter PUF Compositions

Abstract

NEOS Toolset by Kaveh Shamsi (UT-Dallas) and Deep Learning-Based Model Building Attacks on Arbiter PUF Compositions by Rajat Subhra Chakraborty (IIT Kharagpur) and Pranesh Santikellur (IIT Kharagpur).

The CAD for Trust and Assurance website is an academic dissemination effort by researchers in the field of hardware security. The goal is to assemble information on all CAD for trust/assurance activities in academia and industry in one place and share them with the broader community of researchers and practitioners in a timely manner, with an easy-to-search and easy-to-access interface. We’re including information on many major CAD tools the research community has developed over the past decade, including open-source license-free or ready-for-licensing tools, associated metrics, relevant publications, and video-demos. We are also delighted to announce that a series of virtual CAD for Assurance tool training webinars starting in February 2021.

Additional information on these webinars is available at the CAD for Assurance website at https://cadforassurance.org/​.