Home › Entities › academia › A 0.26% BER, 10<sup>28</sup> Challenge-Response Machine-Learning Resistant Strong-PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection

A 0.26% BER, 10<sup>28</sup> Challenge-Response Machine-Learning Resistant Strong-PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection

Research article (2020 IEEE Symposium on VLSI Circuits, 2020) · cited 20× · AI/ML
academia openalex:W3048728216
Press Enter · cited answer in seconds

A 0.26% BER, 1028 Challenge-Response Machine-Learning Resistant Strong-PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection

Summary

A 0.26% BER, 1028 Challenge-Response Machine-Learning Resistant Strong-PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection is a scholarly article[1].

Key Facts

  • A 0.26% BER, 1028 Challenge-Response Machine-Learning Resistant Strong-PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). A 0.26% BER, 10<sup>28</sup> Challenge-Response Machine-Learning Resistant Strong-PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-0-26-ber-10-sup-28-sup-challenge-response-machine-learning-resistant-strong-puf-in-14nm-cmos-featuring-stability-aware
MLA “A 0.26% BER, 10<sup>28</sup> Challenge-Response Machine-Learning Resistant Strong-PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-0-26-ber-10-sup-28-sup-challenge-response-machine-learning-resistant-strong-puf-in-14nm-cmos-featuring-stability-aware.
BibTeX @misc{4ortxyz_a-0-26-ber-10-sup-28-sup-challenge-response-machine-learning-resistant-strong-puf-in-14nm-cmos-featuring-stability-aware_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A 0.26% BER, 10<sup>28</sup> Challenge-Response Machine-Learning Resistant Strong-PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection}}, year = {2026}, url = {https://4ort.xyz/entity/a-0-26-ber-10-sup-28-sup-challenge-response-machine-learning-resistant-strong-puf-in-14nm-cmos-featuring-stability-aware}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A 0.26% BER, 10<sup>28</sup> Challenge-Response Machine-Learning Resistant Strong-PUF in 14nm CMOS Featuring Stability-Aware Adversarial Challenge Selection — https://4ort.xyz/entity/a-0-26-ber-10-sup-28-sup-challenge-response-machine-learning-resistant-strong-puf-in-14nm-cmos-featuring-stability-aware (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/a-0-26-ber-10-sup-28-sup-challenge-response-machine-learning-resistant-strong-puf-in-14nm-cmos-featuring-stability-aware · Last refreshed: