skip to main content
10.1145/3404663.3404664acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicisdmConference Proceedingsconference-collections
research-article

An Inventory of Existing Neuroprivacy Controls

Authors Info & Claims
Published:10 July 2020Publication History

ABSTRACT

Brain-Computer Interfaces (BCIs) facilitate communication between brains and computers. As these devices become increasingly popular outside of the medical context, research interest in brain privacy risks and countermeasures has bloomed. Several neuroprivacy threats have been identified in the literature, including brain malware, personal data being contained in collected brainwaves and the inadequacy of legal regimes with regards to neural data protection. Dozens of controls have been proposed or implemented for protecting neuroprivacy, although it has not been immediately apparent what the landscape of neuroprivacy controls consists of. This paper inventories the implemented and proposed neuroprivacy risk mitigation techniques from open source repositories, BCI providers and the academic literature. These controls are mapped to the Hoepman privacy strategies and their implementation status is described. Several research directions for ensuring the protection of neuroprivacy are identified.

References

  1. Agarwal, A., Dowsley, R., McKinney, N. D., Wu, D., Lin, C.-T., Cock, M. D., & Nascimento, A. (2018). Privacy-preserving linear regression for brain-computer interface applications. Proceedings of the IEEE International Conference on Big Data (Big Data), Seattle, WA. https://doi.org/10.1109/BigData.2018.8621861Google ScholarGoogle ScholarCross RefCross Ref
  2. Agarwal, A., Dowsley, R., McKinney, N. D., Wu, D., Lin, C.-T., Cock, M. D., & Nascimento, A. (2019). Protecting privacy of users in brain-computer interface applications. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(8), 1546--1555. https://doi.org/10.1109/TNSRE.2019.2926965Google ScholarGoogle ScholarCross RefCross Ref
  3. Bak, S., Pyo, Y., & Jeong, J. (2019). Protection of EEG data using blockchain platform. Proceedings of the International Winter Conference on Brain-Computer Interface (BCI), Gangwon, South Korea, 1--3. Piscataway, NJ: IEEE. https://doi.org/10.1109/IWW-BCI.2019.8737260Google ScholarGoogle ScholarCross RefCross Ref
  4. Bernal, S. L., Celdrán, A. H., Pérez, G. M., Barros, M. T., Balasubramaniam, S. (2019). Cybersecurity in brain-computer interfaces: state-of-the-art, opportunities, and future challenges. ArXiv:1908.03536.Google ScholarGoogle Scholar
  5. Bonaci, T., Herron, J., Matlack, C., & Chizeck, H. J. (2014). Securing the exocortex: A twenty-first century cybernetics challenge. Proceedings of the 2014 IEEE Conference on Norbert Wiener in the 21st Century (21CW), Boston, MA. https://doi.org/10.1109/NORBERT.2014.6893912Google ScholarGoogle ScholarCross RefCross Ref
  6. Bonaci, T. (2015). Security and Privacy of Biomedical Cyber-Physical Systems. University of Washington, ProQuest Dissertations and Theses.Google ScholarGoogle Scholar
  7. Brigham, K., & Kumar, B. V. K. (2010). Imagined Speech Classification with EEG Signals for Silent Communication: A Preliminary Investigation into Synthetic Telepathy. Proceedings of the International Conference on Bioinformatics and Biomedical Engineering, Chengdu, China, 1--4. Piscataway, NJ: IEEE. https://doi.org/10.1109/ICBBE.2010.5515807Google ScholarGoogle ScholarCross RefCross Ref
  8. Cannon, JC. (2014). Privacy in Technology: Standards and Practices for Engineers and Security and IT Professionals. Portsmouth, NH: International Association of Privacy Professionals.Google ScholarGoogle Scholar
  9. Chizeck, H. J., & Bonaci, T. (2014). U.S. Patent Application No. 14/174,818.Google ScholarGoogle Scholar
  10. Colesky, M., Hoepman, J.-H., & Hillen, C. (2016). A critical analysis of privacy design strategies. 2016 IEEE Security and Privacy Workshops (SPW), San Jose, CA, 33--40. Piscataway, NJ: IEEE. https://doi.org/10.1109/SPW.2016.23Google ScholarGoogle ScholarCross RefCross Ref
  11. Cronk, J. (2018). Strategic privacy by design. Portsmouth, NH: International Association of Privacy Professionals.Google ScholarGoogle Scholar
  12. Dennedy, M. F., Fox J., Finneran, T. (2014). The privacy engineer's manifesto: getting from policy to code to QA to value. New York, NY: ApressGoogle ScholarGoogle ScholarCross RefCross Ref
  13. Denning, T., Matsuoka, Y., & Kohno, T. (2009). Neurosecurity: security and privacy for neural devices. Neurosurgical Focus, 27(1), E7. https://doi.org/10.3171/2009.4.FOCUS0985Google ScholarGoogle ScholarCross RefCross Ref
  14. Dustman, R. E., Shearer, D. E., & Emmerson, R. Y. (1999). Life-span changes in EEG spectral amplitude, amplitude variability and mean frequency. Clinical neurophysiology, 110(8), 1399--1409. https://doi.org/10.1016/s1388-2457(99)00102-9Google ScholarGoogle Scholar
  15. Emotiv. (2018, May 25). EMOTIV privacy policy. EMOTIV. https://id.emotivcloud.com/eoidc/privacy/privacy_policy/Google ScholarGoogle Scholar
  16. Emotiv. (2019). Mobile and Secure EEG Cloud Database. EMOTIV. https://www.emotiv.com/emotiv-eeg-cloud/Google ScholarGoogle Scholar
  17. Finn, R. L., Wright, D., & Friedewald, M. (2013). Seven types of privacy. European data protection: coming of age, 3--32. Dordrecht: Springer. https://doi.org/10.1007/978-94-007-5170-5_1Google ScholarGoogle Scholar
  18. Frank, M. Hwu, T., Jain, S., Knight, R.T., Martinovic, I., Mittal, P., Perito, D., Sluganovic, I., & Song, D. (2017). Using EEG-based BCI devices to subliminally probe for private information. Proceedings of the 2017 Workshop on Privacy in the Electronic Society (WPES'17), Dallas, TX, 133--136. https://doi.org/10.1145/3139550.3139559Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Gladden, M. E. (2017). The Handbook of Information Security for Advanced Neuroprosthetics, (2nd ed.). Indianapolis, IN: Synthypnion Academic.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Hallinan, D., Schütz, P., Friedewald, M., & de Hert, P. (2013). Neurodata and neuroprivacy: Data protection outdated? Surveillance & Society 12(1), 55--72. https://doi.org/10.24908/ss.v12i1.4500Google ScholarGoogle ScholarCross RefCross Ref
  21. Hoepman, J.-H. (2014). Privacy design strategies. Proceedings of the IFIP International Information Security Conference (SEC), Marrakech, Morocco. 446--459. https://doi.org/10.1007/978-3-642-55415-5_38Google ScholarGoogle ScholarCross RefCross Ref
  22. Hoepman, J.-H. (2019). Privacy design strategies (the little blue book). Groningen: De Privacy Coach. https://www.cs.ru.nl/J.H.Hoepman/publications/pds-booklet.pdfGoogle ScholarGoogle Scholar
  23. Ienca, M. (2015). Neuroprivacy, neurosecurity and brain-hacking: Emerging issues in neural engineering. Bioethica Forum. 8(2), 51--53. Schwabe.Google ScholarGoogle Scholar
  24. Ienca, M., & Haselager, P. (2016). Hacking the brain: brain--computer interfacing technology and the ethics of neurosecurity. Ethics and Information Technology, 18(2), 117--129. https://doi.org/10.1007/s10676-016-9398-9Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Inzlicht, M., McGregor, I., Hirsh, J. B., & Nash, K. (2009). Neural markers of religious conviction. Psychological Science, 20(3), 385--392. https://doi.org/10.1111/j.1467-9280.2009.02305.xGoogle ScholarGoogle ScholarCross RefCross Ref
  26. Kokoon. (2019). Privacy policy. Kokoon. https://kokoon.io/policies/privacy-policyGoogle ScholarGoogle Scholar
  27. Li, Q., Ding, D., & Conti, M. (2015). Brain-computer interface applications: Security and privacy challenges. Proceedings of the 2015 IEEE Conference on Communications and Network Security (CNS), Florence, Italy. https://doi.org/10.1109/CNS.2015.7346884Google ScholarGoogle Scholar
  28. Martinovic, I., Davies, D., Frank, M., Perito, D., Ros, T., & Song, D. (2012). On the feasibility of side-channel attacks with brain-computer interfaces. Proceedings of the 21st USENIX Security Symposium, Bellevue, WA, 143--158. https://www.usenix.org/conference/usenixsecurity12/technical-sessions/presentation/martinovicGoogle ScholarGoogle ScholarDigital LibraryDigital Library
  29. Muse. (2019, April 27). Privacy policy. muse. https://choosemuse.com/legal/Google ScholarGoogle Scholar
  30. NeuroSky. (2018, May 25). Effective learner privacy policy. Effective Learner Cloud. https://effectivelearnercloud.com/el/policies/?privacyGoogle ScholarGoogle Scholar
  31. The Committee on Science and Law. (2005). Are your thoughts your own? Neuroprivacy and the legal implications of brain imaging. New York, NY: New York City Bar Association.Google ScholarGoogle Scholar
  32. Github. (2018, June 27). Open brain consent. Github Blob. https://github.com/con/open-brain-consent/blob/master/docs/source/ultimate.rstGoogle ScholarGoogle Scholar
  33. P.N. Rao, R. (2013). Brain-computer interfacing: an introduction. Cambridge: Cambridge University Press.Google ScholarGoogle ScholarCross RefCross Ref
  34. Sempreboni, D., & Viganò, L. (2018). Privacy, security and trust in the internet of neurons. ArXiv:1807.06077.Google ScholarGoogle Scholar
  35. Solove, D. J. (2006). A taxonomy of privacy. University of Pennsylvania Law Review, 154, 477--560.Google ScholarGoogle ScholarCross RefCross Ref
  36. Spiekermann, S., & Cranor, L. F. (2009). Engineering privacy. IEEE Transactions on Software Engineering, 35(1), 67--82. https://doi.org/10.1109/TSE.2008.88Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Stopczynski, A., Greenwood, D., Hansen, L. K., & Pentland, A. (2014, April 21). Privacy for personal neuroinformatics. SSRN Electronic Journal. https://doi.org/10.2139/ssm.2427564Google ScholarGoogle Scholar
  38. Takabi, H. (2016). Firewall for brain: towards a privacy preserving ecosystem for BCI applications. Proceedings of the 2016 IEEE Conference on Communications and Network Security (CNS), Philadelphia, PA. https://doi.org/10.1109/CNS.2016.7860516Google ScholarGoogle ScholarCross RefCross Ref
  39. Takabi, H., Bhalotiya, A., & Alohaly, M. (2016). Brain computer interface (BCI) applications: privacy threats and countermeasures. Proceedings of the International Conference on Collaboration and Internet Computing (CIC), Pittsburgh, PA, 102--111. Piscataway, NJ: IEEE. https://doi.org/10.1109/CIC.2016.026Google ScholarGoogle ScholarCross RefCross Ref
  40. Wu, D., Lawhern, V. J., Gordon, S., Lance, B. J., & Lin, C. (2017). Driver drowsiness estimation from EEG signals using Online weighted Adaptation Regularization for Regression (OwARR). IEEE Transactions on Fuzzy Systems, 25(6), 1522--1535. https://doi.org/10.1109/TFUZZ.2016.2633379Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Zhang, S., Yuan, S., Huang, L., Zheng, X., Wu, Z., Xu, K., & Pan, G. (2019). Human mind control of rat cyborg's continuous locomotion with wireless brain-to-brain interface. Scientific reports, 9(1), 1--12. https://doi.org/10.1038/s41598-018-36885-0Google ScholarGoogle Scholar

Index Terms

  1. An Inventory of Existing Neuroprivacy Controls

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      ICISDM '20: Proceedings of the 2020 the 4th International Conference on Information System and Data Mining
      May 2020
      170 pages
      ISBN:9781450377652
      DOI:10.1145/3404663

      Copyright © 2020 ACM

      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]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 10 July 2020

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed limited

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader