# Logic Locking at the Frontiers of Machine Learning: A Survey on Developments and Opportunities

arXiv: https://arxiv.org/abs/2107.01915 · HTML: https://mlsanity.com/paper/2107.01915/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 48 references that are in the map.
- First posted on arXiv 5 Jul 2021.

## Builds on (most cited first, 12 of 12)

- [The Cost of Application-Class Processing: Energy and Performance Analysis of a Linux-ready 1.7GHz 64bit RISC-V Core in 22nm FDSOI Technology](https://mlsanity.com/paper/1904.05442/) (2019)
- [SAIL: Machine Learning Guided Structural Analysis Attack on Hardware Obfuscation](https://mlsanity.com/paper/1809.10743/) (2018)
- [Challenging the Security of Logic Locking Schemes in the Era of Deep Learning: A Neuroevolutionary Approach](https://mlsanity.com/paper/2011.10389/) (2020)
- [GNNUnlock: Graph Neural Networks-based Oracle-less Unlocking Scheme for Provably Secure Logic Locking](https://mlsanity.com/paper/2012.05948/) (2020)
- [Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning](https://mlsanity.com/paper/1902.05357/) (2019)
- [UNSAIL: Thwarting Oracle-Less Machine Learning Attacks on Logic Locking](https://mlsanity.com/paper/2012.14938/) (2020)
- [Threats on Logic Locking: A Decade Later](https://mlsanity.com/paper/1905.05896/) (2019)
- [NNgSAT: Neural Network guided SAT Attack on Logic Locked Complex Structures](https://mlsanity.com/paper/2009.02208/) (2020)
- [ASSURE: RTL Locking Against an Untrusted Foundry](https://mlsanity.com/paper/2010.05344/) (2020)
- [Deep RNN-Oriented Paradigm Shift through BOCANet: Broken Obfuscated Circuit Attack](https://mlsanity.com/paper/1803.03332/) (2018)
- [Attack of the Genes: Finding Keys and Parameters of Locked Analog ICs Using Genetic Algorithm](https://mlsanity.com/paper/2003.13904/) (2020)
- [Scalable Attack-Resistant Obfuscation of Logic Circuits](https://mlsanity.com/paper/2010.15329/) (2020)

## 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)

In the past decade, a lot of progress has been made in the design and evaluation of logic locking; a premier technique to safeguard the integrity of integrated circuits throughout the electronics supply chain. However, the widespread proliferation of machine learning has recently introduced a new pathway to evaluating logic locking schemes. This paper summarizes the recent developments in logic locking attacks and countermeasures at the frontiers of contemporary machine learning models. Based on the presented work, the key takeaways, opportunities, and challenges are highlighted to offer recommendations for the design of next-generation logic locking.