References

Here you can see the references that appear in the project report:

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  • Li, Q., Ding, D. & Conti, M. Brain-computer interface applications: Security and privacy challenges. In 2015 IEEE conference on communications and network security (CNS), 663–666 (IEEE, 2015).
  • Denning, T., Matsuoka, Y. & Kohno, T. Neurosecurity: security and privacy for neural devices. Neurosurg. Focus. 27, E7 (2009).
  • Ienca, M. & Haselager, P. Hacking the brain: brain–computer interfacing technology and the ethics of neurosecurity. Ethics Inf. Technol. 18, 117–129 (2016).
  • Chaudhary, U., Xia, B., Silvoni, S., Cohen, L. G. & Birbaumer, N. Brain–computer interface–based communication in the completely locked-in state. PLoS biology 15, e1002593 (2017).
  • Yadav, D., Yadav, S. & Veer, K. A comprehensive assessment of brain computer interfaces: Recent trends and challenges. J. Neurosci. Methods 108918, DOI: https://doi.org/10.1016/j.jneumeth.2020.108918 (2020).
  • Camara, C., Peris-Lopez, P. & Tapiador, J. E. Security and privacy issues in implantable medical devices: A comprehensive survey. J. biomedical informatics 55, 272–289 (2015).
  • ENISA. Baseline Security Reccommendations for IoT in the context of crititcal information infrastructures (2017).
  • Halperin, D. et al. Pacemakers and implantable cardiac defibrillators: Software radio attacks and zero-power defenses. In 2008 IEEE Symposium on Security and Privacy (sp 2008), 129–142 (IEEE, 2008).
  • FDA warns patients, providers about cybersecurity concerns with certain Medtronic implantable cardiac devices. https://www.fda.gov/NewsEvents/Newsroom/FDAInBrief/ucm623191.htm
  • Marin, E. et al. On the (in) security of the latest generation implantable cardiac defibrillators and how to secure them. In Proceedings of the 32nd annual conference on computer security applications, 226–236 (2016).
  • Slotwiner, D. J. et al. Cybersecurity vulnerabilities of cardiac implantable electronic devices: Communication strategies for clinicians—proceedings of the heart rhythm society’s leadership summit. Hear. rhythm 15, e61–e67 (2018).
  • Pugh, J., Pycroft, L., Sandberg, A., Aziz, T. Z. & Savulescu, J. Brainjacking in deep brain stimulation and autonomy. Ethics Inf. Technol. 20, 219–232, DOI: 10.1007/s10676-018-9466-4 (2018).
  • Commision, F. T. Internet of Things – New security and privacy challenges. Federal Trade Commision, Washington, DC (2010).
  • Buzsaki, G. Rhythms of the Brain (Oxford University Press, 2006).
  • ROSENBLUM, M. et al. Detection of phase locking from noisy data: application to magnetoencephalography. In Chaos In Brain?, 34–51 (World Scientific, 2000).
  • Boccaletti, S., Latora, V., Moreno, Y., Chavez, M. & Hwang, D.-U. Complex networks: Structure and dynamics. Phys. reports 424, 175–308 (2006).
  • Bullmore, E. & Sporns, O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. reviews neuroscience 10, 186–198 (2009).
  • Daly, I., Nasuto, S. J. & Warwick, K. Brain computer interface control via functional connectivity dynamics. Pattern recognition 45, 2123–2136 (2012).
  • Zheng, G., Shankaran, R., Orgun, M. A., Qiao, L. & Saleem, K. Ideas and challenges for securing wireless implantable medical devices: A review. IEEE Sensors J. 17, 562–576 (2016).
  • Dolev, D. & Yao, A. On the security of public key protocols. IEEE Transactions on Inf. Theory 29, 198–208 (1983).
  • Wang, W. & Hu, L. Efficient and provably secure generic construction of three-party password-based authenticated key exchange protocols. In Barua, R. & Lange, T. (eds.) Progress in Cryptology – INDOCRYPT 2006, 118–132 (Springer Berlin Heidelberg, Berlin, Heidelberg, 2006).
  • Blanchet, B. Modeling and verifying security protocols with the applied pi calculus and ProVerif. Foundations Trends Priv. Secur. 1, 1–135 (2016).
  • Cremers, C. J. F. The Scyther tool: Verification, falsification, and analysis of security protocols. In Computer Aided Verification, 414–418 (Springer Berlin Heidelberg, 2008).
  • González-Manzano, L., de Fuentes, J. M., Pastrana, S., Peris-Lopez, P. & Hernández-Encinas, L. Pagiot-Privacy-preserving aggregation protocol for internet of things. J. Netw. Comput. Appl. 71, 59–71 (2016).
  • Camara, C., Peris-Lopez, P., Martín, H. & Naser, M. ECG-RNG: A random number generator based on ECG signals and suitable for securing wireless sensor networks. Sensors 18, 2747, DOI: 10.3390/s18092747 (2018).
  • Ortiz-Martin, L., Picazo-Sanchez, P., Peris-Lopez, P. & Tapiador, J. Heartbeats do not make good pseudo-random number generators: an analysis of the randomness of inter-pulse intervals. Entropy 20, 94 (2018).
  • Camara, C., Peris-Lopez, P., Gonzalez-Manzano, L. & Tapiador, J. Real-time electrocardiogram streams for continuous authentication. Appl. Soft Comput. 68, 784–794 (2018).
  • Camara, C., Peris-Lopez, P., De Fuentes, J. M. & Marchal, S. Access control for implantable medical devices. IEEE Transactions on Emerg. Top. Comput. 1–1 (2020).