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On the Security of Smartphone Unlock PINs

Published:30 September 2021Publication History
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Abstract

In this article, we provide the first comprehensive study of user-chosen four- and six-digit PINs (n=1705) collected on smartphones with participants being explicitly primed for device unlocking. We find that against a throttled attacker (with 10, 30, or 100 guesses, matching the smartphone unlock setting), using six-digit PINs instead of four-digit PINs provides little to no increase in security and surprisingly may even decrease security. We also study the effects of blocklists, where a set of “easy to guess” PINs is disallowed during selection. Two such blocklists are in use today by iOS, for four digits (274 PINs) as well as six digits (2,910 PINs). We extracted both blocklists and compared them with six other blocklists, three for each PIN length. In each case, we had a small (four-digit: 27 PINs; six-digit: 29 PINs), a large (four-digit: 2,740 PINs; six-digit: 291,000 PINs), and a placebo blocklist that always excluded the first-choice PIN. For four-digit PINs, we find that the relatively small blocklist in use today by iOS offers little to no benefit against a throttled guessing attack. Security gains are only observed when the blocklist is much larger. In the six-digit case, we were able to reach a similar security level with a smaller blocklist. As the user frustration increases with the blocklists size, developers should employ a blocklist that is as small as possible while ensuring the desired security. Based on our analysis, we recommend that for four-digit PINs a blocklist should contain the 1,000 most popular PINs to provide the best balance between usability and security and for six-digit PINs the 2,000 most popular PINs should be blocked.

References

  1. Oleg Afonin. 2020. iPhone 5 and 5c Passcode Unlock with iOS Forensic Toolkit. Retrieved May 14, 2021 from https://blog.elcomsoft.com/2020/08/iphone-5-and-5c-passcode-unlock-with-ios-forensic-toolkit/Google ScholarGoogle Scholar
  2. Devdatta Akhawe and Adrienne Porter Felt. 2013. Alice in warningland: A large-scale field study of browser security warning effectiveness. In Proceedings of the USENIX Security Symposium. USENIX, 257–272.Google ScholarGoogle Scholar
  3. Daniel Amitay. 2011. Most Common iPhone Passcodes. Retrieved May 14, 2021 from http://danielamitay.com/blog/2011/6/13/most-common-iphone-passcodes.Google ScholarGoogle Scholar
  4. Android Open Source Project. 2018. Full-Disk Encryption—Storing the Encrypted Key. Retrieved May 14, 2021 from https://source.android.com/security/encryption/full-disk#storing_the_encrypted_key.Google ScholarGoogle Scholar
  5. Android Open Source Project. 2020. Android 11: GateKeeper. Retrieved May 14, 2021 from https://android.googlesource.com/platform/system/gatekeeper/+/refs/heads/android11-release/gatekeeper.cpp#268.Google ScholarGoogle Scholar
  6. Apple, Inc.2021. Apple Platform Security. Retrieved May 14, 2021 from https://manuals.info.apple.com/MANUALS/1000/MA1902/en_US/apple-platform-security-guide.pdf.Google ScholarGoogle Scholar
  7. Adam J. Aviv, Devon Budzitowski, and Ravi Kuber. 2015. Is bigger better? Comparing user-generated passwords on 3x3 vs. 4x4 grid sizes for android’s pattern unlock. In Proceedings of the Annual Computer Security Applications Conference. ACM, 301–310.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Adam J. Aviv, John T. Davin, Flynn Wolf, and Ravi Kuber. 2017. Towards baselines for shoulder surfing on mobile authentication. In Proceedings of the Annual Conference on Computer Security Applications. ACM, 486–498.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Adam J. Aviv, Katherine Gibson, Evan Mossop, Matt Blaze, and Jonathan M. Smith. 2010. Smudge attacks on smartphone touch screens. In Proceedings of the USENIX Workshop on Offensive Technologies. USENIX, 1–7.Google ScholarGoogle Scholar
  10. Adam J. Aviv, Flynn Wolf, and Ravi Kuber. 2018. Comparing video based shoulder surfing with live simulation and towards baselines for shoulder surfing on mobile authentication. In Proceedings of the Annual Conference on Computer Security Applications. ACM, 453–466.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Farid Binbeshr, Miss Laiha Mat Kiah, Lip Yee Por, and A. A. Zaidan. 2021. A systematic review of pin-entry methods resistant to shoulder-surfing attacks. Comput. Secur. 101 (Feb. 2021).Google ScholarGoogle Scholar
  12. Joseph Bonneau. 2012. The science of guessing: analyzing an anonymized corpus of 70 million passwords. In Proceedings of the IEEE Symposium on Security and Privacy. IEEE, 538–552.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Joseph Bonneau, Sören Preibusch, and Ross Anderson. 2012. A birthday present every eleven wallets? the security of customer-chosen banking PINs. In Financial Cryptography and Data Security. Springer, 25–40.Google ScholarGoogle Scholar
  14. Thomas Brewster. 2018. Mysterious $15,000 “GrayKey” Promises To Unlock iPhone X For The Feds. Retrieved May 14, 2021 from https://www.forbes.com/sites/thomasbrewster/2018/03/05/apple-iphone-x-graykey-hack/.Google ScholarGoogle Scholar
  15. Thomas Brewster. 2018. The Feds Can Now (Probably) Unlock Every iPhone Model In Existence. Retrieved May 14, 2021 from https://www.forbes.com/sites/thomasbrewster/2018/02/26/government-can-access-any-apple-iphone-cellebrite/.Google ScholarGoogle Scholar
  16. Maria Casimiro, Joe Segel, Lewei Li, Yigeng Wang, and Lorrie Faith Cranor. 2020. A quest for inspiration: How users create and reuse PINs. In Who Are You?! Adventures in Authentication Workshop. 1–7.Google ScholarGoogle Scholar
  17. Ivan Cherapau, Ildar Muslukhov, Nalin Asanka, and Konstantin Beznosov. 2015. On the impact of touch ID on iPhone passcodes. In Proceedings of the Symposium on Usable Privacy and Security. USENIX, 257–276.Google ScholarGoogle Scholar
  18. Justin Engler and Paul Vines. 2013. Electromechanical PIN Cracking with Robotic Reconfigurable Button Basher (and C3BO). Retrieved May 14, 2021 from https://doi.org/10.5446/38941.Google ScholarGoogle Scholar
  19. Adrienne Porter Felt, Alex Ainslie, Robert W. Reeder, Sunny Consolvo, Somas Thyagaraja, Alan Bettes, Helen Harris, and Jeff Grimes. 2015. Improving SSL warnings: Comprehension and adherence. In Proceedings of the ACM Conference on Human Factors in Computing Systems. ACM, 2893–2902.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Maximilian Golla, Dennis Detering, and Markus Dürmuth. 2017. EmojiAuth: Quantifying the security of emoji-based authentication. In Proceedings of the Workshop on Usable Security. ISOC.Google ScholarGoogle ScholarCross RefCross Ref
  21. Maximilian Golla and Markus Dürmuth. 2018. On the accuracy of password strength meters. In Proceedings of the ACM Conference on Computer and Communications Security. ACM, 1567–1582.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Maximilian Golla, Jan Rimkus, Adam J. Aviv, and Markus Dürmuth. 2019. Work in progress: on the in-accuracy and influence of android pattern strength meters. In Proceedings of the Workshop on Usable Security and Privacy. ISOC.Google ScholarGoogle ScholarCross RefCross Ref
  23. Maximilian Golla, Miranda Wei, Juliette Hainline, Lydia Filipe, Markus Dürmuth, Elissa Redmiles, and Blase Ur. 2018. “What was that site doing with my facebook password?” Designing password-reuse notification. In Proceedings of the ACM Conference on Computer and Communications Security. ACM, 1549–1566.Google ScholarGoogle Scholar
  24. Jeremi M. Gosney (“epixoip”). 2016. How LinkedIn’s Password Sloppiness Hurts Us All. Retrieved May 14, 2021 from https://arstechnica.com/?post_type=post&p=892339.Google ScholarGoogle Scholar
  25. Paul A. Grassi, James L. Fenton, and William E. Burr. 2017. Digital Identity Guidelines—Authentication and Lifecycle Management: NIST Special Publication 800-63B.Google ScholarGoogle Scholar
  26. Kristen K. Greene, Melissa A. Gallagher, Brian C. Stanton, and Paul Y. Lee. 2014. I can’t type that! P@$$w0rd entry on mobile devices. In Human Aspects of Information Security, Privacy, and Trust. Springer, 160–171.Google ScholarGoogle Scholar
  27. Gregor Haas, Seetal Potluri, and Aydin Aysu. 2021. iTimed: Cache attacks on the apple a10 fusion SoC. Cryptology ePrint Archive Report 2021/464 (April 2021), 1–16.Google ScholarGoogle Scholar
  28. Marian Harbach, Emanuel von Zezschwitz, Andreas Fichtner, Alexander De Luca, and Matthew Smith. 2014. It’s a hard lock life: A field study of smartphone (Un)Locking behavior and risk perception. In Proceedings of the Symposium on Usable Privacy and Security. USENIX, 213–230.Google ScholarGoogle Scholar
  29. Andrew Horton (“urbanadventurer”) and Community. 2020. Android-PIN-Bruteforce – Bruteforcing the Lockscreen PIN. Retrieved May 14, 2021 from https://github.com/urbanadventurer/Android-PIN-Bruteforce.Google ScholarGoogle Scholar
  30. Troy Hunt. 2020. Pwned Passwords. Retrieved May 14, 2021 https://haveibeenpwned.com/Passwords.Google ScholarGoogle Scholar
  31. Patrick Kelley, Saranga Kom, Michelle L. Mazurek, et al. 2012. Guess again (and again and again): Measuring password strength by simulating password-cracking algorithms. In Proceedings of the IEEE Symposium on Security and Privacy. IEEE, 523–537.Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Hassan Khan, Jason Ceci, Jonah Stegman, Adam J. Aviv, Rozita Dara, and Ravi Kuber. 2020. Widely reused and shared, infrequently updated, and sometimes inherited: A holistic view of PIN authentication in digital lives and beyond. In Proceedings of the Annual Computer Security Applications Conference. ACM, 249–262.Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Hyoungshick Kim and Jun Ho Huh. 2012. PIN selection policies: Are they really effective?Comput. Secur. 31, 4 (Jun. 2012), 484–496.Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Oleksiy Lisovets, David Knichel, Thorben Moos, and Amir Moradi. 2021. Let’s take it offline: Boosting brute-force attacks on iPhone’s user authentication through SCA. IACR Trans. Cryptogr. Hardw. Embed. Syst. 2021, 3 (Jun. 2021), 1–24.Google ScholarGoogle Scholar
  35. Marte Løge, Markus Dürmuth, and Lillian Røstad. 2016. On user choice for android unlock patterns. In Proceedings of the European Workshop on Usable Security. ISOC.Google ScholarGoogle ScholarCross RefCross Ref
  36. Philipp Markert, Daniel V. Bailey, Maximilian Golla, Markus Dürmuth, and Adam J. Aviv. 2020. This PIN can be easily guessed: Analyzing the security of smartphone unlock PINs. In Proceedings of the IEEE Symposium on Security and Privacy. IEEE, 286–303.Google ScholarGoogle Scholar
  37. William Melicher, Darya Kurilova, Sean M. Segreti, Pranshu Kalvani, Richard Shay, Blase Ur, Lujo Bauer, Nicolas Christin, Lorrie Faith Cranor, and Michelle L. Mazurek. 2016. Usability and security of text passwords on mobile devices. In Proceedings of the ACM Conference on Human Factors in Computing Systems. ACM, 527–539.Google ScholarGoogle Scholar
  38. Saif M. Mohammad and Peter D. Turney. 2013. Crowdsourcing a word-emotion association lexicon. Comput. Intell. 29, 3 (2013), 436–465.Google ScholarGoogle ScholarCross RefCross Ref
  39. Collins W. Munyendo, Miles Grant, Philipp Markert, Timothy J. Forman, and Adam J. Aviv. 2021. Using a blocklist to improve the security of user selection of android patterns. In Proceedings of the Symposium on Usable Privacy and Security. USENIX, 1–19.Google ScholarGoogle Scholar
  40. Ellen Nakashima and Reed Albergotti. 2021. Australian Firm Azimuth Unlocked the San Bernardino Shooter’s iPhone for the FBI. Retrieved May 14, 2021 from https://www.washingtonpost.com/technology/2021/04/14/azimuth-san-bernardino-apple-iphone-fbi/.Google ScholarGoogle Scholar
  41. Lily Hay Newman. 2019. Google’s Making it Easier to Encrypt Even Cheap Android Phones. Retrieved May 14, 2021 from https://www.wired.com/story/android-encryption-cheap-smartphones/.Google ScholarGoogle Scholar
  42. Lina Qiu, Alexander De Luca, Ildar Muslukhov, and Konstantin Beznosov. 2019. Towards understanding the link between age and smartphone authentication. In Proceedings of the ACM Conference on Human Factors in Computing Systems. ACM, 163:1–163:10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Elissa M. Redmiles, Yasemin Acar, Sascha Fahl, and Michelle L. Mazurek. 2017. A Summary of Survey Methodology Best Practices for Security and Privacy Researchers. Technical Report CS-TR-5055. UM Computer Science Department.Google ScholarGoogle Scholar
  44. Thomas Reed. 2018. GrayKey iPhone Unlocker Poses Serious Security Concerns. Retrieved May 2021 from https://blog.malwarebytes.com/?p=22342.Google ScholarGoogle Scholar
  45. Karen Renaud and Melanie Volkamer. 2015. Exploring mental models underlying PIN management strategies. In Proceedings of the World Congress on Internet Security. IEEE, 19–21.Google ScholarGoogle ScholarCross RefCross Ref
  46. Florian Schaub, Ruben Deyhle, and Michael Weber. 2012. Password entry usability and shoulder surfing susceptibility on different smartphone platforms. In Proceedings of the International Conference on Mobile and Ubiquitous Multimedia. ACM, 13:1–13:10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Richard Shay, Lujo Bauer, Nicolas Christin, Lorrie Faith Cranor, Alain Forget, Saranga Komanduri, Michelle L. Mazurek, William Melicher, Sean M. Segreti, and Blase Ur. 2015. A spoonful of sugar?: The impact of guidance and feedback on password-creation behavior. In Proceedings of the ACM Conference on Human Factors in Computing Systems. ACM, 2903–2912.Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Sergei Skorobogatov. 2017. The bumpy road towards iphone 5c NAND mirroring. In Proceedings of the Hardware Security Conference & Training (HardwearIO’17). 1–55.Google ScholarGoogle Scholar
  49. Emily Stark. 2019. The URLephant. In Proceedings of the USENIX Enigma Conference. USENIX.Google ScholarGoogle Scholar
  50. Joshua Sunshine, Serge Egelman, Hazim Almuhimedi, Neha Atri, and Lorrie Faith Cranor. 2009. Crying wolf: An empirical study of SSL warning effectiveness. In Proceedings of the USENIX Security Symposium. USENIX, 399–416.Google ScholarGoogle Scholar
  51. Joshua Tan, Lujo Bauer, Nicolas Christin, and Lorrie Faith Cranor. 2020. Practical recommendations for stronger, more usable passwords combining minimum-strength, minimum-length, and blocklist requirements. In Proceedings of the ACM Conference on Computer and Communications Security. ACM, 1407–1426.Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. Sebastian Uellenbeck, Markus Dürmuth, Christopher Wolf, and Thorsten Holz. 2016. Quantifying the security of graphical passwords: The case of android unlock patterns. In Proceedings of the ACM Conference on Computer and Communications Security. ACM, 161–172.Google ScholarGoogle Scholar
  53. Blase Ur, Felicia Alfieri, Maung Aung, Lujo Bauer, Nicolas Christin, Jessica Colnago, Lorrie Faith Cranor, Henry Dixon, Pardis Emami Naeini, Hana Habib, Noah Johnson, and William Melicher. 2017. Design and evaluation of a data-driven password meter. In Proceedings of the ACM Conference on Human Factors in Computing Systems. ACM, 3775–3786.Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. Blase Ur, Fumiko Noma, Jonathan Bees, Sean M. Segreti, Richard Shay, Lujo Bauer, Nicolas Christin, and Lorrie Faith Cranor. 2015. “I added ‘!’ at the end to make it secure”: Observing password creation in the lab. In Proceedings of the Symposium on Usable Privacy and Security. USENIX, 123–140.Google ScholarGoogle Scholar
  55. Blase Ur, Sean M. Segreti, Lujo Bauer, Nicolas Christin, Lorrie Faith Cranor, Saranga Komanduri, Darya Kurilova, Michelle L. Mazurek, William Melicher, and Richard Shay. 2015. Measuring real-world accuracies and biases in modeling password guessability. In Proceedings of the USENIX Security Symposium. USENIX, 463–481.Google ScholarGoogle Scholar
  56. U.S. Department of Homeland Security. 2012. The Menlo Report. Retrieved May 14, 2021 from https://www.caida.org/publications/papers/2012/menlo_report_actual_formatted/.Google ScholarGoogle Scholar
  57. Emanuel von Zezschwitz, Alexander De Luca, and Heinrich Hussmann. 2014. Honey, i shrunk the keys: Influences of mobile devices on password composition and authentication performance. In Proceedings of the Nordic Conference on Human-Computer Interaction. ACM, 461–470.Google ScholarGoogle ScholarDigital LibraryDigital Library
  58. Emanuel von Zezschwitz, Malin Eiband, Daniel Buschek, Sascha Oberhuber, Alexander De Luca, Florian Alt, and Heinrich Hussmann. 2016. On quantifying the effective passsword space of grid-based unlock gestures. In Proceedings of the Conference on Mobile and Ubiquitous Multimedia. ACM, 201–212.Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. Ding Wang, Qianchen Gu, Xinyi Huang, and Ping Wang. 2017. Understanding human-chosen PINs: Characteristics, distribution and security. In Proceedings of the ACM Asia Conference on Computer and Communications Security. ACM, 372–385.Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. Gareth Watts (“gwatts”) and Community. 2015. Pinfinder—iOS Screen Time & Restrictions Passcode Finder. Retrieved May 14, 2021 from https://github.com/gwatts/pinfinder.Google ScholarGoogle Scholar
  61. Chris Welch. 2018. Apple Releases iOS 11.4.1 and Blocks Passcode Cracking Tools Used by Police. Retrieved May 14, 2021 from https://www.theverge.com/2018/7/9/17549538/.Google ScholarGoogle Scholar
  62. Sonia Secher Wichmann. 2011. Self-determination theory: The importance of autonomy to well-being across cultures. J. Humanist. Counsel. 50, 1 (Mar. 2011), 16–26.Google ScholarGoogle ScholarCross RefCross Ref
  63. Yulong Yang, Janne Lindqvist, and Antti Oulasvirta. 2014. Text entry method affects password security. In Learning from Authoritative Security Experiment Results. USENIX, 11–20.Google ScholarGoogle Scholar

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        cover image ACM Transactions on Privacy and Security
        ACM Transactions on Privacy and Security  Volume 24, Issue 4
        November 2021
        295 pages
        ISSN:2471-2566
        EISSN:2471-2574
        DOI:10.1145/3476876
        Issue’s Table of Contents

        Copyright © 2021 Owner/Author

        This work is licensed under a Creative Commons Attribution International 4.0 License.

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 30 September 2021
        • Accepted: 1 June 2021
        • Revised: 1 May 2021
        • Received: 1 January 2021
        Published in tops Volume 24, Issue 4

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