# Advancing Hardware Security Using Polymorphic and Stochastic Spin-Hall Effect Devices

arXiv: https://arxiv.org/abs/1806.00790 · HTML: https://mlsanity.com/paper/1806.00790/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jun 2018.

## Built on by (most cited first, 1 of 1)

- [Graph Neural Networks: A Powerful and Versatile Tool for Advancing Design, Reliability, and Security of ICs](https://mlsanity.com/paper/2211.16495/) (2022)

## Abstract (arXiv)

Protecting intellectual property (IP) in electronic circuits has become a serious challenge in recent years. Logic locking/encryption and layout camouflaging are two prominent techniques for IP protection. Most existing approaches, however, particularly those focused on CMOS integration, incur excessive design overheads resulting from their need for additional circuit structures or device-level modifications. This work leverages the innate polymorphism of an emerging spin-based device, called the giant spin-Hall effect (GSHE) switch, to simultaneously enable locking and camouflaging within a single instance. Using the GSHE switch, we propose a powerful primitive that enables cloaking all the 16 Boolean functions possible for two inputs. We conduct a comprehensive study using state-of-the-art Boolean satisfiability (SAT) attacks to demonstrate the superior resilience of the proposed primitive in comparison to several others in the literature. While we tailor the primitive for deterministic computation, it can readily support stochastic computation; we argue that stochastic behavior can break most, if not all, existing SAT attacks. Finally, we discuss the resilience of the primitive against various side-channel attacks as well as invasive monitoring at runtime, which are arguably even more concerning threats than SAT attacks.