# MLMSA: Multi-Label Multi-Side-Channel-Information enabled Deep Learning Attacks on APUF Variants

arXiv: https://arxiv.org/abs/2207.09744 · HTML: https://mlsanity.com/paper/2207.09744/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Jul 2022.

## Built on by (most cited first, 3 of 3)

- [A novel reliability attack of Physical Unclonable Functions](https://mlsanity.com/paper/2405.13147/) (2024)
- [Lightweight Strategy for XOR PUFs as Security Primitives for Resource-constrained IoT device](https://mlsanity.com/paper/2210.01749/) (2022)
- [Designing Short-Stage CDC-XPUFs: Balancing Reliability, Cost, and Security in IoT Devices](https://mlsanity.com/paper/2409.17902/) (2024)

## Abstract (arXiv)

To improve the modeling resilience of silicon strong physical unclonable functions (PUFs), in particular, the APUFs, that yield a very large number of challenge response pairs (CRPs), a number of composited APUF variants such as XOR-APUF, interpose-PUF (iPUF), feed-forward APUF (FF-APUF),and OAX-APUF have been devised. When examining their security in terms of modeling resilience, utilizing multiple information sources such as power side channel information (SCI) or/and reliability SCI given a challenge is under-explored, which poses a challenge to their supposed modeling resilience in practice. Building upon multi-label/head deep learning model architecture,this work proposes Multi-Label Multi-Side-channel-information enabled deep learning Attacks (MLMSA) to thoroughly evaluate the modeling resilience of aforementioned APUF variants. Despite its simplicity, MLMSA can successfully break large-scaled APUF variants, which has not previously been achieved. More precisely, the MLMSA breaks 128-stage 30-XOR-APUF, (9, 9)- and (2, 18)-iPUFs, and (2, 2, 30)-OAX-APUF when CRPs, power SCI and reliability SCI are concurrently used. It breaks 128-stage 12-XOR-APUF and (2, 2, 9)-OAX-APUF even when only the easy-to-obtain reliability SCI and CRPs are exploited. The 128-stage six-loop FF-APUF and one-loop 20-XOR-FF-APUF can be broken by simultaneously using reliability SCI and CRPs. All these attacks are normally completed within an hour with a standard personalcomputer. Therefore, MLMSA is a useful technique for evaluating other existing or any emerging strong PUF designs.