DRV-fingerprinting: Using data retention voltage of SRAM cells for chip identification

Daniel E. Holcomb; Amir Rahmati; Mastooreh Salajegheh; Wayne P. Burleson; Kevin Fu

doi:10.1007/978-3-642-36140-1_12

DRV-fingerprinting: Using data retention voltage of SRAM cells for chip identification

Daniel E. Holcomb
, Amir Rahmati
, Mastooreh Salajegheh
, Wayne P. Burleson
, Kevin Fu

Computer Science

University of California at Berkeley
University of Massachusetts

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

21 Scopus citations

Abstract

Physical unclonable functions (PUFs) produce outputs that are a function of minute random physical variations. Promoted for low-cost authentication and resistance to counterfeiting, many varieties of PUFs have been used to enhance the security and privacy of RFID tags. To different extents, applications for both identification and authentication require a PUF to produce a consistent output over time. As the sensing of minute variations is a fundamentally noisy process, much effort is spent on error correction of PUF outputs. We propose a new variant of PUF that uses well-understood properties of common memory cells as a fingerprint. Our method of fingerprinting SRAM cells by their data retention voltage improves the success rate of identification by 28% over fingerprints based on power-up state.

Original language	English
Title of host publication	Radio Frequency Identification
Subtitle of host publication	Security and Privacy Issues - 8th International Workshop, RFIDSec 2012, Revised Selected Papers
Publisher	Springer Verlag
Pages	165-179
Number of pages	15
ISBN (Print)	9783642361395
DOIs	https://doi.org/10.1007/978-3-642-36140-1_12
State	Published - 2013
Event	8th International Workshop on Radio Frequency Identification: Security and Privacy Issues, RFIDSec 2012 - Nijmegen, Netherlands Duration: Jul 2 2012 → Jul 3 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7739 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Workshop on Radio Frequency Identification: Security and Privacy Issues, RFIDSec 2012
Country/Territory	Netherlands
City	Nijmegen
Period	07/2/12 → 07/3/12

Access to Document

10.1007/978-3-642-36140-1_12

Cite this

Holcomb, D. E., Rahmati, A., Salajegheh, M., Burleson, W. P., & Fu, K. (2013). DRV-fingerprinting: Using data retention voltage of SRAM cells for chip identification. In Radio Frequency Identification: Security and Privacy Issues - 8th International Workshop, RFIDSec 2012, Revised Selected Papers (pp. 165-179). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7739 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-642-36140-1_12

Holcomb, Daniel E. ; Rahmati, Amir ; Salajegheh, Mastooreh et al. / DRV-fingerprinting : Using data retention voltage of SRAM cells for chip identification. Radio Frequency Identification: Security and Privacy Issues - 8th International Workshop, RFIDSec 2012, Revised Selected Papers. Springer Verlag, 2013. pp. 165-179 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "DRV-fingerprinting: Using data retention voltage of SRAM cells for chip identification",

abstract = "Physical unclonable functions (PUFs) produce outputs that are a function of minute random physical variations. Promoted for low-cost authentication and resistance to counterfeiting, many varieties of PUFs have been used to enhance the security and privacy of RFID tags. To different extents, applications for both identification and authentication require a PUF to produce a consistent output over time. As the sensing of minute variations is a fundamentally noisy process, much effort is spent on error correction of PUF outputs. We propose a new variant of PUF that uses well-understood properties of common memory cells as a fingerprint. Our method of fingerprinting SRAM cells by their data retention voltage improves the success rate of identification by 28\% over fingerprints based on power-up state.",

author = "Holcomb, \{Daniel E.\} and Amir Rahmati and Mastooreh Salajegheh and Burleson, \{Wayne P.\} and Kevin Fu",

year = "2013",

doi = "10.1007/978-3-642-36140-1\_12",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

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}

Holcomb, DE, Rahmati, A, Salajegheh, M, Burleson, WP & Fu, K 2013, DRV-fingerprinting: Using data retention voltage of SRAM cells for chip identification. in Radio Frequency Identification: Security and Privacy Issues - 8th International Workshop, RFIDSec 2012, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7739 LNCS, Springer Verlag, pp. 165-179, 8th International Workshop on Radio Frequency Identification: Security and Privacy Issues, RFIDSec 2012, Nijmegen, Netherlands, 07/2/12. https://doi.org/10.1007/978-3-642-36140-1_12

DRV-fingerprinting: Using data retention voltage of SRAM cells for chip identification. / Holcomb, Daniel E.; Rahmati, Amir; Salajegheh, Mastooreh et al.
Radio Frequency Identification: Security and Privacy Issues - 8th International Workshop, RFIDSec 2012, Revised Selected Papers. Springer Verlag, 2013. p. 165-179 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7739 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - DRV-fingerprinting

T2 - 8th International Workshop on Radio Frequency Identification: Security and Privacy Issues, RFIDSec 2012

AU - Holcomb, Daniel E.

AU - Rahmati, Amir

AU - Salajegheh, Mastooreh

AU - Burleson, Wayne P.

AU - Fu, Kevin

PY - 2013

Y1 - 2013

N2 - Physical unclonable functions (PUFs) produce outputs that are a function of minute random physical variations. Promoted for low-cost authentication and resistance to counterfeiting, many varieties of PUFs have been used to enhance the security and privacy of RFID tags. To different extents, applications for both identification and authentication require a PUF to produce a consistent output over time. As the sensing of minute variations is a fundamentally noisy process, much effort is spent on error correction of PUF outputs. We propose a new variant of PUF that uses well-understood properties of common memory cells as a fingerprint. Our method of fingerprinting SRAM cells by their data retention voltage improves the success rate of identification by 28% over fingerprints based on power-up state.

AB - Physical unclonable functions (PUFs) produce outputs that are a function of minute random physical variations. Promoted for low-cost authentication and resistance to counterfeiting, many varieties of PUFs have been used to enhance the security and privacy of RFID tags. To different extents, applications for both identification and authentication require a PUF to produce a consistent output over time. As the sensing of minute variations is a fundamentally noisy process, much effort is spent on error correction of PUF outputs. We propose a new variant of PUF that uses well-understood properties of common memory cells as a fingerprint. Our method of fingerprinting SRAM cells by their data retention voltage improves the success rate of identification by 28% over fingerprints based on power-up state.

UR - https://www.scopus.com/pages/publications/84873377598

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DO - 10.1007/978-3-642-36140-1_12

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Holcomb DE, Rahmati A, Salajegheh M, Burleson WP, Fu K. DRV-fingerprinting: Using data retention voltage of SRAM cells for chip identification. In Radio Frequency Identification: Security and Privacy Issues - 8th International Workshop, RFIDSec 2012, Revised Selected Papers. Springer Verlag. 2013. p. 165-179. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-36140-1_12

DRV-fingerprinting: Using data retention voltage of SRAM cells for chip identification

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