Secret-key capacity regions for multiple enrollments with an SRAM-PUF

C.J. Kusters (Corresponding author), F.M.J. Willems

Research output: Contribution to journalArticleAcademicpeer-review

31 Downloads (Pure)

Abstract

We introduce the multiple enrollment scheme for SRAM-PUFs. During each enrollment the binary power-on values of the SRAM are observed, and a corresponding key and helper data are generated. Each key can later be reconstructed from an additional observation and the helper data. The helper data do not reveal information about the keys to an attacker. It is our goal to use the additional enrollments to consecutively increase the entropy of the generated key material.

We analyze two alternative settings. First, we present a regular setting, where each additional key is independent of all previous keys. Secondly, we introduce a key-replacement setting, where instead of an additional independent key, a new key (of increased length) is generated that replaces the old key.
We characterize the capacity regions for both settings. We show that the total achievable secret-key rate is equal to the mutual information between all enrollment observations and a single (reconstruction) observation.

We derive our results based on a statistical model for SRAM-PUF that has been proposed in the literature. This model implies a \textit{permutation symmetry} property of SRAM-PUF which plays a key role in our proofs.
Original languageEnglish
Article number8626480
Pages (from-to)2276-2287
Number of pages12
JournalIEEE Transactions on Information Forensics and Security
Volume14
Issue number9
DOIs
Publication statusPublished - Sep 2019

Fingerprint

Static random access storage
Entropy

Keywords

  • SRAM cell
  • Security
  • Internet of Things
  • Secret-key capacity
  • Slepian–Wolf coding

Cite this

@article{4483cd3109bc43c68b367bea21e6911b,
title = "Secret-key capacity regions for multiple enrollments with an SRAM-PUF",
abstract = "We introduce the multiple enrollment scheme for SRAM-PUFs. During each enrollment the binary power-on values of the SRAM are observed, and a corresponding key and helper data are generated. Each key can later be reconstructed from an additional observation and the helper data. The helper data do not reveal information about the keys to an attacker. It is our goal to use the additional enrollments to consecutively increase the entropy of the generated key material.We analyze two alternative settings. First, we present a regular setting, where each additional key is independent of all previous keys. Secondly, we introduce a key-replacement setting, where instead of an additional independent key, a new key (of increased length) is generated that replaces the old key.We characterize the capacity regions for both settings. We show that the total achievable secret-key rate is equal to the mutual information between all enrollment observations and a single (reconstruction) observation.We derive our results based on a statistical model for SRAM-PUF that has been proposed in the literature. This model implies a \textit{permutation symmetry} property of SRAM-PUF which plays a key role in our proofs.",
keywords = "SRAM cell, Security, Internet of Things, Secret-key capacity, Slepian–Wolf coding",
author = "C.J. Kusters and F.M.J. Willems",
year = "2019",
month = "9",
doi = "10.1109/TIFS.2019.2895552",
language = "English",
volume = "14",
pages = "2276--2287",
journal = "IEEE Transactions on Information Forensics and Security",
issn = "1556-6013",
publisher = "Institute of Electrical and Electronics Engineers",
number = "9",

}

Secret-key capacity regions for multiple enrollments with an SRAM-PUF. / Kusters, C.J. (Corresponding author); Willems, F.M.J.

In: IEEE Transactions on Information Forensics and Security, Vol. 14, No. 9, 8626480, 09.2019, p. 2276-2287.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Secret-key capacity regions for multiple enrollments with an SRAM-PUF

AU - Kusters, C.J.

AU - Willems, F.M.J.

PY - 2019/9

Y1 - 2019/9

N2 - We introduce the multiple enrollment scheme for SRAM-PUFs. During each enrollment the binary power-on values of the SRAM are observed, and a corresponding key and helper data are generated. Each key can later be reconstructed from an additional observation and the helper data. The helper data do not reveal information about the keys to an attacker. It is our goal to use the additional enrollments to consecutively increase the entropy of the generated key material.We analyze two alternative settings. First, we present a regular setting, where each additional key is independent of all previous keys. Secondly, we introduce a key-replacement setting, where instead of an additional independent key, a new key (of increased length) is generated that replaces the old key.We characterize the capacity regions for both settings. We show that the total achievable secret-key rate is equal to the mutual information between all enrollment observations and a single (reconstruction) observation.We derive our results based on a statistical model for SRAM-PUF that has been proposed in the literature. This model implies a \textit{permutation symmetry} property of SRAM-PUF which plays a key role in our proofs.

AB - We introduce the multiple enrollment scheme for SRAM-PUFs. During each enrollment the binary power-on values of the SRAM are observed, and a corresponding key and helper data are generated. Each key can later be reconstructed from an additional observation and the helper data. The helper data do not reveal information about the keys to an attacker. It is our goal to use the additional enrollments to consecutively increase the entropy of the generated key material.We analyze two alternative settings. First, we present a regular setting, where each additional key is independent of all previous keys. Secondly, we introduce a key-replacement setting, where instead of an additional independent key, a new key (of increased length) is generated that replaces the old key.We characterize the capacity regions for both settings. We show that the total achievable secret-key rate is equal to the mutual information between all enrollment observations and a single (reconstruction) observation.We derive our results based on a statistical model for SRAM-PUF that has been proposed in the literature. This model implies a \textit{permutation symmetry} property of SRAM-PUF which plays a key role in our proofs.

KW - SRAM cell

KW - Security

KW - Internet of Things

KW - Secret-key capacity

KW - Slepian–Wolf coding

UR - http://www.scopus.com/inward/record.url?scp=85066466828&partnerID=8YFLogxK

U2 - 10.1109/TIFS.2019.2895552

DO - 10.1109/TIFS.2019.2895552

M3 - Article

AN - SCOPUS:85066466828

VL - 14

SP - 2276

EP - 2287

JO - IEEE Transactions on Information Forensics and Security

JF - IEEE Transactions on Information Forensics and Security

SN - 1556-6013

IS - 9

M1 - 8626480

ER -