RSS-Based Secret Key Generation in Wireless In-body Networks

Secure communication is considered as an integral part of next generation wireless implantable medical devices. In this work, we provide the symmetric cryptographic key generating approach by exploiting the randomness in received signal strength (RSS) for data encryption in an in-body network. The application of concern is the wireless modules for next generation leadless cardiac pacemaker with two units. For RSS based key generation method, both the units probe the wireless channel for RSS measurements within the coherence time and outputs the encryption key bits based on available randomness and quantization algorithm. To evaluate the available randomness in RSS measurements, the methodology of phantom experiments is adapted to emulate the cardiac cycle. It has been found that the measurements emulating the cardiac cycle can be approximated to follow the log-Normal distribution. Moreover, a high correlation of RSS measurements is observed across the pacemaker units to generate a symmetric key whereas the eavesdropper link is found to be highly de-correlated. Based on the available randomness, the quantization algorithm generates 2-bits per cardiac cycle and requires 64 cardiac cycles to generate a 128-bit binary key string with an average mismatch percentage of 1 % over 1000 key runs.

[1]  U. Maurer,et al.  Secret key agreement by public discussion from common information , 1993, IEEE Trans. Inf. Theory.

[2]  Juan E. Tapiador,et al.  Security and privacy issues in implantable medical devices: A comprehensive survey , 2015, J. Biomed. Informatics.

[3]  Honorio Martín,et al.  ECG-RNG: A Random Number Generator Based on ECG Signals and Suitable for Securing Wireless Sensor Networks , 2018, Sensors.

[4]  Kimmo Kansanen,et al.  Experimental Phantom-Based Security Analysis for Next-Generation Leadless Cardiac Pacemakers , 2018, Sensors.

[5]  Carmen C. Y. Poon,et al.  A novel biometrics method to secure wireless body area sensor networks for telemedicine and m-health , 2006, IEEE Communications Magazine.

[6]  Kimmo Kansanen,et al.  Experimental phantom-based evaluation of Physical Layer Security for Future Leadless Cardiac Pacemaker , 2018, 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC).

[7]  H. Mond,et al.  The 11th World Survey of Cardiac Pacing and Implantable Cardioverter‐Defibrillators: Calendar Year 2009–A World Society of Arrhythmia's Project , 2011, Pacing and clinical electrophysiology : PACE.

[8]  Syed Taha Ali,et al.  Eliminating Reconciliation Cost in Secret Key Generation for Body-Worn Health Monitoring Devices , 2014, IEEE Transactions on Mobile Computing.

[9]  Gerhard Wunder,et al.  A Novel Key Generating Architecture for Wireless Low-Resource Devices , 2014, 2014 International Workshop on Secure Internet of Things.

[10]  Kevin Fu,et al.  Pacemakers and Implantable Cardiac Defibrillators: Software Radio Attacks and Zero-Power Defenses , 2008, 2008 IEEE Symposium on Security and Privacy (sp 2008).

[11]  Mark Mohammad Tehranipoor,et al.  Highly Reliable Key Generation From Electrocardiogram (ECG) , 2017, IEEE Transactions on Biomedical Engineering.

[12]  Junqing Zhang,et al.  Key Generation From Wireless Channels: A Review , 2016, IEEE Access.

[13]  Thijs Castel,et al.  Encrypted body-to-body wireless sensor node employing channel-state-based key generation , 2016, 2016 10th European Conference on Antennas and Propagation (EuCAP).