On using a von neumann extractor in heart-beat-based security
Paper in proceedings, 2015

The Inter-Pulse-Interval (IPI) of heart beats has previously been suggested for facilitating security in mobile health (mHealth) applications. In heart-beat-based security, a security key is derived from the time difference between consecutive heart beats. As two entities that simultaneously sample the same heart beats may generate the same key (with some inter-key disparity), these keys may be used for various security functions, such as entity authentication or data confidentiality. One of the key limitations in heart-beat-based security is the low randomness intrinsic to the most-significant bits (MSBs) in the digital representation of each IPI. In this paper, we explore the use of a von Neumann entropy extractor on these MSBs in order to increase their randomness. We show that our von Neumann key-generator produces significantly more random bits than a non-extracting key generator with an average bit-extraction rate between 13.4% and 21.9%. Despite this increase in randomness, we also find a substantial increase in inter-key disparity, increasing the mismatch tolerance required for a given true-key pair. Accordingly, the maximum-attainable effective key-strength of our key generator is only slightly higher than that of a non-extracting generator (16.4 bits compared to 15.2 bits of security for a 60-bit key), while the former requires an increase in average key-generation time of 2.5x.

MHealth

Biometrics

Heart-beat-based security

Implantable Medical Devices

Security

Inter-pulse interval

Author

R.M. Seepers

Erasmus University Medical Center

C. Strydis

Erasmus University Medical Center

Ioannis Sourdis

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

C.I. De Zeeuw

Erasmus University Medical Center

Proceedings - 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2015, Helsinki, Finland, 20-22 August 2015

Vol. 1 491-498

Subject Categories

Computer Science

DOI

10.1109/Trustcom.2015.411

ISBN

978-1-4673-7951-9

More information

Created

10/8/2017