skip to main content
10.1145/3196494.3196530acmconferencesArticle/Chapter ViewAbstractPublication Pagesasia-ccsConference Proceedingsconference-collections
research-article

Pseudoentropic Isometries: A New Framework for Fuzzy Extractor Reusability

Published: 29 May 2018 Publication History

Abstract

Fuzzy extractors (Dodiset al., Eurocrypt 2004) turn a noisy secret into a stable, uniformly distributed key. Reusable fuzzy extractors remain secure when multiple keys are produced from a single noisy secret (Boyen, CCS 2004). Boyen showed information-theoretically secure reusable fuzzy extractors are subject to strong limitations. Simoens et al. (IEEE S&P, 2009) then showed deployed constructions suffer severe security breaks when reused. Canetti et al. (Eurocrypt 2016) used computational security to sidestep this problem, building a computationally secure reusable fuzzy extractor that corrects a sublinear fraction of errors.
We introduce a generic approach to constructing reusable fuzzy extractors. We define a new primitive called a reusable pseudoentropic isometry that projects an input metric space to an output metric space. This projection preserves distance and entropy even if the same input is mapped to multiple output metric spaces. A reusable pseudoentropy isometry yields a reusable fuzzy extractor by 1) randomizing the noisy secret using the isometry and 2) applying a traditional fuzzy extractor to derive a secret key.
We propose reusable pseudoentropic isometries for the set difference and Hamming metrics. The set difference construction is built from composable digital lockers (Canetti and Dakdouk, Eurocrypt 2008). For the Hamming metric, we show that the second construction of Canetti et al.(Eurocrypt 2016) can be seen as an instantiation of our framework. In both cases, the pseudoentropic isometry's reusability requires noisy secrets distributions to have entropy in each symbol of the alphabet. Our constructions yield the first reusable fuzzy extractors that correct a constant fraction of errors. We also implement our set difference solution and describe two use cases.

References

[1]
Host-based card emulation. https://developer.android.com/guide/topics/connectivity/nfc/hce.html.
[2]
Most common first names and last names in the u.s. https://names.mongabay.com/male_names.htm.
[3]
Multi-factor authentication. https://www.pcisecuritystandards.org/pdfs/Multi-Factor-Authentication-Guidance-v1.pdf.
[4]
Python implementation of our set difference based RPI. Available at https://github.com/benjaminfuller/CompFE/blob/master/RPISetDifference.py.
[5]
G. Acar, C. Eubank, S. Englehardt, M. Juarez, A. Narayanan, and C. Diaz. The web never forgets: Persistent tracking mechanisms in the wild. In Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, CCS '14, pages 674--689, New York, NY, USA, 2014. ACM.
[6]
J. P. Achara, G. Acs, and C. Castelluccia. On the unicity of smartphone applications. In Proceedings of the 14th ACM Workshop on Privacy in the Electronic Society, WPES '15, pages 27--36. ACM, 2015.
[7]
D. Apon, C. Cho, K. Eldefrawy, and J. Katz. Efficient, reusable fuzzy extractors from lwe. Cryptology ePrint Archive, Report 2017/755, 2017. http://eprint.iacr.org/2017/755.
[8]
Bancontact. SEPA Rulebooks Scheme Manuals Remote Domain 46D0­ Mobile App Security Guidelines, 2016.
[9]
C. H. Bennett, G. Brassard, and J.-M. Robert. Privacy amplification by public discussion. SIAM Journal on Computing, 17(2):210--229, 1988.
[10]
N. Bitansky and R. Canetti. On strong simulation and composable point obfuscation. In Advances in Cryptology--CRYPTO 2010, pages 520--537. Springer, 2010.
[11]
M. Blanton and M. Aliasgari. Analysis of reusability of secure sketches and fuzzy extractors. IEEE Trans. Information Forensics and Security, 8(9):1433--1445, 2013.
[12]
K. Boda, A. M. Földes, G. G. Gulyás, and S. Imre. User tracking on the web via cross-browser fingerprinting. In Proceedings of the 16th Nordic Conference on Information Security Technology for Applications, NordSec'11, pages 31--46, Berlin, Heidelberg, 2012. Springer-Verlag.
[13]
H. Bojinov, Y. Michalevsky, G. Nakibly, and D. Boneh. Mobile device identification via sensor fingerprinting. CoRR, abs/1408.1416, 2014.
[14]
X. Boyen. Reusable cryptographic fuzzy extractors. In Proceedings of the 11th ACM Conference on Computer and Communications Security, CCS '04, pages 82--91. ACM, 2004.
[15]
R. Canetti. Towards realizing random oracles: Hash functions that hide all partial information. In Advances in Cryptology - CRYPTO '97, 17th Annual International Cryptology Conference, Santa Barbara, California, USA, August 17-21, 1997, Proceedings, pages 455--469, 1997.
[16]
R. Canetti and R. R. Dakdouk. Obfuscating point functions with multibit output. In Advances in Cryptology--EUROCRYPT 2008, pages 489--508. Springer, 2008.
[17]
R. Canetti, B. Fuller, O. Paneth, L. Reyzin, and A. Smith. Advances in Cryptology -- EUROCRYPT 2016, chapter Reusable Fuzzy Extractors for Low-Entropy Distributions, pages 117--146. Springer Berlin Heidelberg, Berlin, Heidelberg, 2016.
[18]
R. Canetti, Y. Tauman Kalai, M. Varia, and D. Wichs. On Symmetric Encryption and Point Obfuscation, pages 52--71. Springer Berlin Heidelberg, Berlin, Heidelberg, 2010.
[19]
M. Chen, J. Fridrich, M. Goljan, and J. Lukás. Determining image origin and integrity using sensor noise. IEEE Transactions on Information Forensics and Security, 3(1):74--90, 2008.
[20]
A. Das, N. Borisov, and M. Caesar. Do you hear what i hear?: Fingerprinting smart devices through embedded acoustic components. In Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, CCS '14, pages 441--452, 2014.
[21]
J. Daugman. How iris recognition works. IEEE Transactions on Circuits and Systems for Video Technology, 14:21--30, 2002.
[22]
Y. Dodis, R. Ostrovsky, L. Reyzin, and A. Smith. Fuzzy extractors: How to generate strong keys from biometrics and other noisy data. SIAM J. Comput., 38(1):97--139, Mar. 2008.
[23]
Y. Dodis, L. Reyzin, and A. Smith. Fuzzy extractors: How to generate strong keys from biometrics and other noisy data. In Advances in Cryptology - EUROCRYPT 2004, volume 3027 of Lecture Notes in Computer Science, pages 523--540. Springer Berlin Heidelberg, 2004.
[24]
P. Eckersley. How unique is your web browser? In Privacy Enhancing Technologies, 10th International Symposium, PETS 2010, Berlin, Germany, July 21-23, 2010. Proceedings, pages 1--18, 2010.
[25]
ETSI. Digital cellular telecommunications system (phase 2. Security related network functions, 1992.
[26]
European Parliament. General Data Protection Regulation (GDPR). http://ec.europa.eu/justice/data-protection/reform/files/regulation_oj_en.pdf, 2016.
[27]
B. Fuller, X. Meng, and L. Reyzin. Computational Fuzzy Extractors, pages 174--193. Springer Berlin Heidelberg, Berlin, Heidelberg, 2013.
[28]
J. Galbally, A. Ross, M. Gomez-Barrero, J. Fierrez, and J. Ortega-Garcia. Iris image reconstruction from binary templates: An efficient probabilistic approach based on genetic algorithms. Computer Vision and Image Understanding, 117(10):1512--1525, 2013.
[29]
Gemalto. Gemalto eSE secure end-to-end solutions. https://www.gemalto.com/iot/consumer-electronics/embedded-secure-element.
[30]
GlobalPlatform. GlobalPlatform made simple guide: Trusted Execution Environment (TEE) Guide. https://www.globalplatform.org/mediaguidetee.asp.
[31]
Google. Android Developer Reference, Settings.Secure, ANDROID_ID. https://developer.android.com/reference/android/provider/Settings.Secure.html#ANDROID_ID.
[32]
Google. Android Security 2016 Year in Review. https://source.android.com/security/reports/Google_Android_Security_2016_Report_Final.pdf, 2017.
[33]
K. Harmon, S. Johnson, and L. Reyzin. An implementation of syndrome encoding and decoding for binary bch codes, secure sketches and fuzzy extractors, 2006. Available at http://www.cs.bu.edu/ reyzin/code/fuzzy.html.
[34]
J. Håstad, R. Impagliazzo, L. A. Levin, and M. Luby. A pseudorandom generator from any one-way function. SIAM Journal on Computing, 28(4):1364--1396, 1999.
[35]
C. Herder, B. Fuller, M. van Dijk, and S. Devadas. Public key cryptosystems with noisy secret keys. IACR Cryptology ePrint Archive, 2017:210, 2017.
[36]
C. Herder, L. Ren, M. van Dijk, M.-D. Yu, and S. Devadas. Trapdoor computational fuzzy extractors and stateless cryptographically-secure physical unclonable functions. IEEE Transactions on Dependable and Secure Computing, 14(1):65--82, 2017.
[37]
C.-Y. Hsiao, C.-J. Lu, and L. Reyzin. Conditional computational entropy, or toward separating pseudoentropy from compressibility. In Annual International Conference on the Theory and Applications of Cryptographic Techniques, pages 169--186. Springer, 2007.
[38]
A. Juels and M. Sudan. A fuzzy vault scheme. Des. Codes Cryptography, 38(2):237--257, Feb. 2006.
[39]
A. Juels and M. Wattenberg. A fuzzy commitment scheme. In Proceedings of the 6th ACM Conference on Computer and Communications Security, CCS '99, pages 28--36. ACM, 1999.
[40]
S. Komanduri, R. Shay, P. G. Kelley, M. L. Mazurek, L. Baue r, N. Christin, L. F. Cranor, and S. Egelman. Of passwords and people: measuring the effect of password-composition policies. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 2595--2604. ACM, 2011.
[41]
A. Kurtz, H. Gascon, T. Becker, K. Rieck, and F. Freiling. Fingerprinting mobile devices using personalized configurations. Proceedings on Privacy Enhancing Technologies, 2016(1):4--19, 2016.
[42]
J. Lin, B. Liu, N. M. Sadeh, and J. I. Hong. Modeling users' mobile app privacy preferences: Restoring usability in a sea of permission settings. In Tenth Symposium on Usable Privacy and Security, SOUPS 2014, Menlo Park, CA, USA, July 9-11, 2014, pages 199--212, 2014.
[43]
J. Lukas, J. Fridrich, and M. Goljan. Digital camera identification from sensor pattern noise. IEEE Transactions on Information Forensics and Security, 1(2):205--214, June 2006.
[44]
B. Lynn, M. Prabhakaran, and A. Sahai. Positive results and techniques for obfuscation. In Advances in Cryptology--EUROCRYPT 2004, pages 20--39. Springer, 2004.
[45]
MasterCard. MasterCard CloudBased Payments Security Guidelines for MPA Development Version 1.1, 2015.
[46]
Morpho. Secure Elements. https://www.morpho.com/en/commercial-identity/solutions-telecom/secure-elements.
[47]
K. Mowery and H. Shacham. Pixel perfect: Fingerprinting canvas in HTML5. In M. Fredrikson, editor, Proceedings of W2SP 2012. IEEE Computer Society, May 2012.
[48]
C. Mulliner, R. Borgaonkar, P. Stewin, and J. Seifert. Sms-based one-time passwords: Attacks and defense - (short paper). In Detection of Intrusions and Malware, and Vulnerability Assessment - 10th International Conference, DIMVA 2013, Berlin, Germany, July 18-19, 2013. Proceedings, pages 150--159, 2013.
[49]
N. Nikiforakis, A. Kapravelos, W. Joosen, C. Kruegel, F. Piessens, and G. Vigna. Cookieless monster: Exploring the ecosystem of web-based device fingerprinting. In Proceedings of the 2013 IEEE Symposium on Security and Privacy, SP '13, pages 541--555, Washington, DC, USA, 2013. IEEE Computer Society.
[50]
N. Nisan and D. Zuckerman. Randomness is linear in space. Journal of Computer and System Sciences, 52(1):43--52, 1996.
[51]
NIST. Digital identity guidelines: Authentication and lifecycle management. http://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800--63b.pdf.
[52]
R. Pappu, B. Recht, J. Taylor, and N. Gershenfeld. Physical one-way functions. Science, 297(5589):2026--2030, 2002.
[53]
S. Prabhakar, S. Pankanti, and A. K. Jain. Biometric recognition: Security and privacy concerns. IEEE Security &Privacy, 1(2):33--42, 2003.
[54]
K. Simoens, P. Tuyls, and B. Preneel. Privacy weaknesses in biometric sketches. In 2009 30th IEEE Symposium on Security and Privacy, pages 188--203.
[55]
E. Telecommunications Standards Institute. SIM. http://www.etsi.org/technologies-clusters/technologies/smart-cards/sim.
[56]
U. Uludag, S. Pankanti, S. Prabhakar, and A. K. Jain. Biometric cryptosystems: issues and challenges. Proceedings of the IEEE, 92(6):948--960, June 2004.
[57]
VISA. Security Requirements and Evaluation Guidance for Mobile Applications. Visa Digital Solutions. Version 1.0, 2014.
[58]
Y. Wen, S. Liu, and S. Han. Reusable fuzzy extractor from the decisional diffie--hellman assumption. Designs, Codes and Cryptography, pages 1--18, 2018.
[59]
Wikipedia. International Mobile Equipment Identity (IMEI). https://en.wikipedia.org/wiki/International_Mobile_Equipment_Identity.
[60]
Z. Zhou, W. Diao, X. Liu, and K. Zhang. Acoustic fingerprinting revisited: Generate stable device id stealthily with inaudible sound. In Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, CCS '14, pages 429--440. ACM, 2014.

Cited By

View all

Index Terms

  1. Pseudoentropic Isometries: A New Framework for Fuzzy Extractor Reusability

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    ASIACCS '18: Proceedings of the 2018 on Asia Conference on Computer and Communications Security
    May 2018
    866 pages
    ISBN:9781450355766
    DOI:10.1145/3196494
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 29 May 2018

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. fuzzy extractors
    2. mobile authentication
    3. pseudoentropic isometries
    4. reusability

    Qualifiers

    • Research-article

    Conference

    ASIA CCS '18
    Sponsor:

    Acceptance Rates

    ASIACCS '18 Paper Acceptance Rate 52 of 310 submissions, 17%;
    Overall Acceptance Rate 418 of 2,322 submissions, 18%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)19
    • Downloads (Last 6 weeks)1
    Reflects downloads up to 03 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media