Wireless Datapaths and Security

  • B. Gil
  • H. Ip
  • Guang-Zhong Yang


For Implantable Medical Devices (IMD), we have discussed in the previous chapters the technical challenges related to biocompatible materials, flexible fabrication processes, system-on-chip design, low-power operation, and packaging. Increasingly advanced computing capabilities found in IMDs and networking technologies can further broaden the applications and enhance the functions of these devices. However, they can only make a real impact on healthcare when a high level of security is incorporated in these devices. This chapter discusses the relationship between different components of an IMD security system under intrinsic resource constraints. A qualitative overview of the strategies commonly used to provide a secure implant system is provided and the chapter covers the design considerations of lightweight and no-hardware-intensive algorithms for implants.

List of Acronyms


Control access list


Angle of arrival


Application specific integrated circuit


Body-coupled communication


Cellar automata


Complementary metal-oxide semiconductor


Differential time of arrival


Error correcting codes




European Medicines Agency


ECG-based secret data sharing


Food and Drug Administration


Gate equivalents


Independent-identically distributed


Implantable device


Linear feedback shift register


Learning parity in the presence of noise


Message authentication code


Medical Implant Communication System


Near-field communication


Nonlinear feedback shift register


One-time pads


Public-key infrastructure


Pseudorandom generator


Random access memory




Radiofrequency identification


Random number


Received signal strength indicator


Random variable


Secure hash algorithm




Universal software radio peripheral


Wireless Medical Telemetry Services


  1. 1.
    S. Hosseini-Khayat, A lightweight security protocol for ultra-low power ASIC implementation for wireless medical devices, in IEEE 5th International Conference on Medical Information & Communication Technology (ISMICT), pp. 6–9 (2011)Google Scholar
  2. 2.
    C. Camara et al., Security and privacy issues in implantable medical devices: a comprehensive survey. J. Biomed. Inform. 55, 272–289 (2015)CrossRefGoogle Scholar
  3. 3.
    X. Hei et al., PIPAC: patient infusion pattern based access control scheme for wireless insulin pump system, in IEEE Proceedings INFOCOM, pp. 3030–3038 (2013)Google Scholar
  4. 4.
    M. Zhang et al., Trustworthiness of medical devices and body area networks. Proc. IEEE 102(8) (2014)Google Scholar
  5. 5.
    H. Martin et al., An estimator for the ASIC footprint area of lightweight cryptographic algorithms. IEEE Trans. Ind. Inf. 10(2) (2014)Google Scholar
  6. 6.
    Q. Yang et al., An on-chip security guard based on zero-power authentication for implantable medical devices, in IEEE 57th International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 531–534 (2014)Google Scholar
  7. 7.
    K. Daniluk E.N. Szynkiewicz, Energy-efficient security in implantable medical devices, in IEEE Proceedings of the Federal Conference on Computer Science and Systems (FedCSIS), pp. 773–778 (2012)Google Scholar
  8. 8.
    M. Rushanan et al., SoK: security and privacy in implantable medical devices and body area networks, in IEEE 14th Symposium on Security and Privacy, pp. 524–539 (2014)Google Scholar
  9. 9.
    D. Halperin et al., Pacemakers and implantable cardiac defibrillators: software radio attacks and zero-power defences, in IEEE Symposium on Security and Privacy, pp. 129–142 (2008)Google Scholar
  10. 10.
    C. Li et al., Hijacking an insulin pump: security attacks and defences for a diabetes therapy system, in IEEE 13th International Conference on e-Health Networking Applications and Software (Healthcom), pp. 150–156 (2011)Google Scholar
  11. 11.
    M. Rostami et al., Balancing security and utility in medical devices?, in ACM/EDAC/IEEE 50th Design Automation Conference (DAC), pp. 1–6 (2013)Google Scholar
  12. 12.
    X. Hei, X. Du, Biometric-based two-level secure access control for implantable medical devices during emergencies, in IEEE Proceedings on INFOCOM, pp. 346–350 (2011)Google Scholar
  13. 13.
    Z. Ankarali et al., A comparative review on the wireless implantable medical devices privacy and security, in EAI 4th International Conference on Wireless Mobile Communication and Healthcare (Mobihealth), pp. 246–249 (2014)Google Scholar
  14. 14.
    G. Zheng et al., Securing wireless medical implants using an ECG-based secret data sharing scheme, in IEEE International Symposium on Communications and Information Technologies (ISCIT), 2014Google Scholar
  15. 15.
    G. Zheng et al., Encryption for implantable medical devices using modified one-time pads. IEEE Open Access J. 3, 825–836 (2015)CrossRefGoogle Scholar
  16. 16.
    T. Denning et al., Absence makes the heart grow fonder: new directions for implantable medical devices security, in Proceedings 3rd Conference on Hot Topics in Security, no. 5, USENIX Association, 2008Google Scholar
  17. 17.
    S. Gollakota et al., IMD Shield: Securing Implantable Medical Devices (Poster) (USENIX Association, 2011)Google Scholar
  18. 18.
    G. Zheng et al., A non-key based security scheme supporting emergency treatment of wireless implants, in IEEE ICC Symposium on Communication and Information Systems Security, 2014Google Scholar
  19. 19.
    F. Xu et al., IMDGuard: securing implantable medical devices with the external wearable guardian, in IEEE Proceedings on INFOCOM, pp. 1862–1870 (2011)Google Scholar
  20. 20.
    M. Zhang et al., MedMon: securing medical devices through wireless monitoring and anomaly detection. IEEE Trans. Biomed. Circuits Syst. 7(6), 2013Google Scholar
  21. 21.
    M. O’Neill, M.J.B. Robshaw, Low-cost digital signature architecture suitable for radio frequency identification tags. IET Comput. Digit. Tech. 4(1), 14–26 (2010)CrossRefGoogle Scholar
  22. 22.
    A. Juels, Minimalist cryptography for low-cost RFID tags, in Proceedings International Conference Security in Communication Networks CSN 2004, Amalfi, ItalyGoogle Scholar
  23. 23.
    J.H. Oh et al., A light-weight security protocol for RFID system, in 7th IEEE International Conference on Computer and Information Technology, 2007Google Scholar
  24. 24.
    M. Burmester, J. Munilla, Lightweight RFID authentication with forward and backward security, in ACM Transactions on Information and Systems Security, May 2011Google Scholar
  25. 25.
    D. Coppersmith et al., The shrinking generator, Proceedings Advances in Cryptology (LNCS, Springer, Berlin, 1993) pp. 22–39 Google Scholar
  26. 26.
    N.J. Hopper, M. Blum, Secure human identification protocols, in Proceedings 7th International Conference on the Theory and Application of Cryptology and Information Security: advances in Cryptology, ed. by C. Boyd, pp. 52–66 (2001)Google Scholar
  27. 27.
    H. Gilbert et al., HB#: increasing the security and efficiency of HB+, Lecture notes in Computer Science, vol 4965 (Springer, Berlin, 2008), pp. 361–378Google Scholar
  28. 28.
    M. S. Mamum, A. Miyaji, A fully-secure RFID authentication protocol from exact LPN assumption, in Proceedings IEEE International Conference on Trust, Security, and Privacy in Computing and Communications, 2013Google Scholar
  29. 29.
    A. Jain et al., Commitments and efficient zero-knowledge proofs from learning parity with noise. ASIACRYPT 2012 Lect. Notes Comput. Sci. 7658, 663–680 (2012)MathSciNetzbMATHGoogle Scholar
  30. 30.
    A. Shamir, SQUASH—a new MAC with provable security properties for highly constrained devices such as RFID tags, in Proceedings Fast Software Encryption, pp. 144–157 (2008)Google Scholar
  31. 31.
    S. Wolfram, A New Kind of Science (Wolfram Media Inc., Champaign, IL, 2002)Google Scholar
  32. 32.
    S. Wolfram, Cryptography with cellular automata. Lecture Notes in Computer Science, vol 218 (Springer, Berlin, 1986), pp. 429–432Google Scholar
  33. 33.
    C.K. Koc, A.M. Apohan, Inversion of cellular automata iterations. IEEE Proc. Comput. Digital Tech. 144(5), 279–284 (1997)CrossRefGoogle Scholar
  34. 34.
    P. Ping et al., Image encryption based on non-affine and balanced cellular automata. Sig. Process. 105, 419–429 (2015)CrossRefGoogle Scholar
  35. 35.
    S.R. Blackburn et al., Comments on—theory and applications of cellular automata in cryptography. IEEE Trans. Comput. 46(5), 637–639 (1997)MathSciNetCrossRefGoogle Scholar
  36. 36.
    M. Scaban et al., Collective behaviour of rules for cellular automata-based stream ciphers, in Proceedings Congress Evolutionary Computation, Vancouver, 2006Google Scholar
  37. 37.
    M. Seredynski et al., Reversible cellular automata based encryption, Lecture Notes in Computer Science, vol 3222, pp. 411–418 (2004)Google Scholar
  38. 38.
    G. Alvarex et al., A secure scheme to share secret color images. Comput. Phys. Commun. 173(1–2) (2005)Google Scholar
  39. 39.
    R.J. Chen, J.L. Lai, Image security system using recursive cellular automata substitution. Pattern Recognit. 40(5), 1621–1631 (2007)Google Scholar
  40. 40.
    E. Pasalic, C. Carlet, Algebraic attacks and decomposition of Boolean functions, in Proceedings EUROCRYPT, Lecture Notes in Computer Science, vol 3027, pp. 474–491, 2204Google Scholar
  41. 41.
    J.C. Castro et al., The strict avalanche criterion randomness test. Math. Comput. Simul. 68, 1–7 (2005)MathSciNetCrossRefzbMATHGoogle Scholar
  42. 42.
    T. Siegenthaler, Correlation-immunity of nonlinear combining functions for cryptographic applications, in IEEE Transactions on Information Theory, 31, 1985Google Scholar
  43. 43.
    N. Courtois, W. Meier, Algebraic attacks on stream ciphers with linear feedback, Advances in Cryptology, EUROCRYPT 2003, Lecture Notes in Computer Science, vol 2656 (Springer, Berlin, 2003), pp. 346–359Google Scholar
  44. 44.
    N.T. Courtois, Higher order correlation attacks, XL algorithm and cryptanalysis of toyocrypt. Inf. Secur. Cryptol. Proc. ICISC 2002 Lect. Notes Comput. Sci. 2587, 182–199 (2002)MathSciNetzbMATHGoogle Scholar
  45. 45.
    L.R. Simpson et al., LILI keystream generator. Lect. Notes Comput. Sci. 2012, 248–261 (2001)MathSciNetCrossRefzbMATHGoogle Scholar
  46. 46.
    N. Courtois, J. Pieprzyk, Cryptanalysis of block ciphers with overdefined systems of equations. ASIACRYPT 2002 Lect. Notes Comput. Sci. 2501, 267–287 (2002)MathSciNetzbMATHGoogle Scholar
  47. 47.
    C. Berbain et al., Cryptanalysis of Grain, in Proceedings FSE’06, Lecture Notes in Computer Science, vol 4047 (2006)Google Scholar
  48. 48.
    M. Hell et al., Grain—a stream cipher for constrained environments. ECRYPT 2005 Int. J. Wireless Mobile Comput. 2(1), 86–93 (2007)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.The Hamlyn CentreImperial College LondonLondonUK

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