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KEHKey: Kinetic Energy Harvester-based Authentication and Key Generation for Body Area Network

Published: 18 March 2020 Publication History

Abstract

For kinetic-powered body area networks, we explore the feasibility of converting energy harvesting patterns for device authentication and symmetric secret keys generation continuously. The intuition is that at any given time, multiple wearable devices harvest kinetic energy from the same user activity, such as walking, which allows them to independently observe a common secret energy harvesting pattern not accessible to outside devices. Such continuous KEH-based authentication and key generation is expected to be highly power efficient as it obviates the need to employ any extra sensors, such as accelerometer, to precisely track the walking patterns. Unfortunately, lack of precise activity tracking introduces bit mismatches between the independently generated keys, which makes KEH-based authentication and symmetric key generation a challenging problem. We propose KEHKey, a KEH-based authentication and key generation system that employs a compressive sensing-based information reconciliation protocol for wearable devices to effectively correct any mismatches in generated keys. We implement KEHKey using off-the-shelf piezoelectric energy harvesting products and evaluate its performance with data collected from 24 subjects wearing the devices on different body locations including head, torso and hands. Our results show that KEHKey is able to generate the same key for two KEH-embedded devices at a speed of 12.57 bps while reducing energy consumption by 59% compared to accelerometer-based methods, which makes it suitable for continuous operation. Finally, we demonstrate that KEHKey can successfully defend against typical adversarial attacks. In particular, KEHKey is found to be more resilient to video side channel attacks than its accelerometer-based counterparts.

References

[1]
Ampy. http://www.getampy.com/ampy-move.html//.
[2]
BionicPower. https://www.bionic-power.com/. Accessed: 2017-10-21.
[3]
InStep Nanopower. http://www.instepnanopower.com/Default.aspx. Accessed: 2017-10-23.
[4]
Mide. https://www.mide.com/.
[5]
ReVibe Energy. http://revibeenergy.com/. Accessed: 2017-10-21.
[6]
H. J. Ailisto, M. Lindholm, J. Mantyjarvi, E. Vildjiounaite, and S.-M. Makela, "Identifying people from gait pattern with accelerometers," in Defense and Security. International Society for Optics and Photonics, 2005, pp. 7--14.
[7]
T. Althoff, J. L. Hicks, A. C. King, S. L. Delp, J. Leskovec et al., "Large-scale physical activity data reveal worldwide activity inequality," Nature, vol. 547, no. 7663, p. 336, 2017.
[8]
R. G. Baraniuk, "Compressive sensing [lecture notes]," IEEE signal processing magazine, vol. 24, no. 4, pp. 118--121, 2007.
[9]
E. Barker, "Nist special publication 800-57 part 1 revision 4, recommendation for key management part 1: General," NIST, 2016.
[10]
L. E. Bassham III, A. L. Rukhin, J. Soto, J. R. Nechvatal, M. E. Smid, E. B. Barker, S. D. Leigh, M. Levenson, M. Vangel, D. L. Banks et al., "Sp 800-22 rev. 1a. a statistical test suite for random and pseudorandom number generators for cryptographic applications," 2010.
[11]
M. Bellare, R. Canetti, and H. Krawczyk, "Keying hash functions for message authentication," in Crypto, vol. 96. Springer, 1996, pp. 1--15.
[12]
D. Bichler, G. Stromberg, M. Huemer, and M. Löw, "Key generation based on acceleration data of shaking processes," UbiComp 2007: Ubiquitous Computing, pp. 304--317, 2007.
[13]
A. Bruesch, L. Nguyen, D. Schürmann, S. Sigg, and L. C. Wolf, "Security properties of gait for mobile device pairing," IEEE Transactions on Mobile Computing, 2019.
[14]
E. J. Candes and T. Tao, "Near-optimal signal recovery from random projections: Universal encoding strategies?" IEEE transactions on information theory, vol. 52, no. 12, pp. 5406--5425, 2006.
[15]
G. C. Clark Jr and J. B. Cain, Error-correction coding for digital communications. Springer Science & Business Media, 2013.
[16]
C. Cornelius and D. Kotz, "Recognizing whether sensors are on the same body," in International Conference on Pervasive Computing. Springer, 2011, pp. 332--349.
[17]
M. Frank, R. Biedert, E. Ma, I. Martinovic, and D. Song, "Touchalytics: On the applicability of touchscreen input as a behavioral biometric for continuous authentication," IEEE transactions on information forensics and security, vol. 8, no. 1, pp. 136--148, 2013.
[18]
D. Gafurov, E. Snekkenes, and P. Bours, "Gait authentication and identification using wearable accelerometer sensor," in 2007 IEEE Workshop on Automatic Identification Advanced Technologies, June 2007, pp. 220--225.
[19]
D. Gafurov, K. Helkala, and T. Søndrol, "Biometric gait authentication using accelerometer sensor." JCP, vol. 1, no. 7, pp. 51--59, 2006.
[20]
D. Gafurov, E. Snekkenes, and T. Buvarp, "Robustness of biometric gait authentication against impersonation attack," in On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops. Springer, 2006, pp. 479--488.
[21]
D. Halperin, T. S. Heydt-Benjamin, B. Ransford, S. S. Clark, B. Defend, W. Morgan, K. Fu, T. Kohno, and W. H. Maisel, "Pacemakers and implantable cardiac defibrillators: Software radio attacks and zero-power defenses," in Security and Privacy, 2008. SP 2008. IEEE Symposium on. IEEE, 2008, pp. 129--142.
[22]
J. Han and B. Bhanu, "Individual recognition using gait energy image," IEEE transactions on pattern analysis and machine intelligence, vol. 28, no. 2, pp. 316--322, 2006.
[23]
C. Harrison, D. Tan, and D. Morris, "Skinput: appropriating the body as an input surface," in Proceedings of the SIGCHI conference on human factors in computing systems. ACM, 2010, pp. 453--462.
[24]
S. Hiremath, G. Yang, and K. Mankodiya, "Wearable internet of things: Concept, architectural components and promises for person-centered healthcare," in Wireless Mobile Communication and Healthcare (Mobihealth), 2014 EAI 4th International Conference on. IEEE, 2014, pp. 304--307.
[25]
C. Hu, X. Cheng, F. Zhang, D. Wu, X. Liao, and D. Chen, "Opfka: Secure and efficient ordered-physiological-feature-based key agreement for wireless body area networks," in INFOCOM, 2013 Proceedings IEEE. IEEE, 2013, pp. 2274--2282.
[26]
A. Kale, A. Sundaresan, A. Rajagopalan, N. P. Cuntoor, A. K. Roy-Chowdhury, V. Kruger, and R. Chellappa, "Identification of humans using gait," IEEE Transactions on image processing, vol. 13, no. 9, pp. 1163--1173, 2004.
[27]
S. Khalifa, M. Hassan, and A. Seneviratne, "Feasibility and accuracy of hotword detection using vibration energy harvester," in World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2016 IEEE 17th International Symposium on A. IEEE, 2016, pp. 1--9.
[28]
S. Khalifa, G. Lan, M. Hassan, A. Seneviratne, and S. K. Das, "Harke: Human activity recognition from kinetic energy harvesting data in wearable devices," IEEE Transactions on Mobile Computing, vol. 17, no. 6, pp. 1353--1368, 2018.
[29]
D. Kirovski, M. Sinclair, and D. Wilson, "The martini synch," Technical Report MSR-TR-2007-123, Microsoft Research, 2007.
[30]
M. Kubo, R. C. Wagenaar, E. Saltzman, and K. G. Holt, "Biomechanical mechanism for transitions in phase and frequency of arm and leg swing during walking," Biological cybernetics, vol. 91, no. 2, pp. 91--98, 2004.
[31]
A. D. Kuo, "Harvesting energy by improving the economy of human walking," Science, vol. 309, no. 5741, pp. 1686--1687, 2005.
[32]
T. Lam and R. Lee, "A new representation for human gait recognition: Motion silhouettes image (msi)," Advances in Biometrics, pp. 612--618, 2005.
[33]
G. Lan, W. Xu, S. Khalifa, M. Hassan, and W. Hu, "Veh-com: Demodulating vibration energy harvesting for short range communication," in Pervasive Computing and Communications (PerCom), 2017 IEEE International Conference on. IEEE, 2017, pp. 170--179.
[34]
E. Lefeuvre, A. Badel, C. Richard, L. Petit, and D. Guyomar, "A comparison between several vibration-powered piezoelectric generators for standalone systems," Sensors and Actuators A: Physical, vol. 126, no. 2, pp. 405--416, 2006.
[35]
J. Lester, B. Hannaford, and G. Borriello, "?are you with me??-using accelerometers to determine if two devices are carried by the same person," in International Conference on Pervasive Computing. Springer, 2004, pp. 33--50.
[36]
Z. Liu and S. Sarkar, "Improved gait recognition by gait dynamics normalization," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 6, pp. 863--876, 2006.
[37]
H. Lu, J. Huang, T. Saha, and L. Nachman, "Unobtrusive gait verification for mobile phones," in Proceedings of the 2014 ACM international symposium on wearable computers. ACM, 2014, pp. 91--98.
[38]
D. Ma, G. Lan, W. Xu, M. Hassan, and W. Hu, "Sehs: Simultaneous energy harvesting and sensing using piezoelectric energy harvester," in Internet-of-Things Design and Implementation (IoTDI), 2018 IEEE/ACM Third International Conference on. IEEE, 2018, pp. 201--212.
[39]
S. Mathur, R. Miller, A. Varshavsky, W. Trappe, and N. Mandayam, "Proximate: proximity-based secure pairing using ambient wireless signals," in Proceedings of the 9th international conference on Mobile systems, applications, and services. ACM, 2011, pp. 211--224.
[40]
S. Mathur, W. Trappe, N. Mandayam, C. Ye, and A. Reznik, "Radio-telepathy: extracting a secret key from an unauthenticated wireless channel," in Mobicom. ACM, 2008, pp. 128--139.
[41]
R. Mayrhofer and H. Gellersen, "Shake well before use: Authentication based on accelerometer data," in International Conference on Pervasive Computing. Springer, 2007, pp. 144--161.
[42]
P. Misra, W. Hu, M. Yang, and S. Jha, "Efficient cross-correlation via sparse representation in sensor networks," in Proceedings of the 11th international conference on Information Processing in Sensor Networks. ACM, 2012, pp. 13--24.
[43]
M. P. Murray, "Gait as a total pattern of movement: Including a bibliography on gait." American Journal of Physical Medicine & Rehabilitation, vol. 46, no. 1, pp. 290--333, 1967.
[44]
C. Nickel, T. Wirtl, and C. Busch, "Authentication of smartphone users based on the way they walk using k-nn algorithm," in Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2012 Eighth International Conference on. IEEE, 2012, pp. 16--20.
[45]
C. C. Poon, Y.-T. Zhang, and S.-D. Bao, "A novel biometrics method to secure wireless body area sensor networks for telemedicine and m-health," IEEE Communications Magazine, vol. 44, no. 4, pp. 73--81, 2006.
[46]
L. Qi, W. Xu, J. Liu, A. Khamis, W. Hu, M. Hassan, and A. Seneviratne, "H2b: Heartbeat-based secret key generation using piezo vibration sensors," in 2019 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). IEEE, 2019.
[47]
Y. Ren, Y. Chen, M. C. Chuah, and J. Yang, "Smartphone based user verification leveraging gait recognition for mobile healthcare systems," in Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2013 10th Annual IEEE Communications Society Conference on. IEEE, 2013, pp. 149--157.
[48]
G. Revadigar, C. Javali, W. Hu, and S. Jha, "Dlink: Dual link based radio frequency fingerprinting for wearable devices," in Local Computer Networks (LCN), 2015 IEEE 40th Conference on. IEEE, 2015, pp. 329--337.
[49]
G. Revadigar, C. Javali, W. Xu, A. V. Vasilakos, W. Hu, and S. Jha, "Accelerometer and fuzzy vault based secure group key generation and sharing protocol for smart wearables," IEEE Transactions on Information Forensics and Security, 2017.
[50]
L. C. Rome, L. Flynn, E. M. Goldman, and T. D. Yoo, "Generating electricity while walking with loads," Science, vol. 309, no. 5741, pp. 1725--1728, 2005.
[51]
M. Rostami, A. Juels, and F. Koushanfar, "Heart-to-heart (h2h): authentication for implanted medical devices," in Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security. ACM, 2013, pp. 1099--1112.
[52]
M. Rushanan, A. D. Rubin, D. F. Kune, and C. M. Swanson, "Sok: Security and privacy in implantable medical devices and body area networks," in Security and Privacy (SP), 2014 IEEE Symposium on. IEEE, 2014, pp. 524--539.
[53]
D. Schürmann, A. Brüsch, S. Sigg, and L. Wolf, "Bandana-body area network device-to-device authentication using natural gait," in Pervasive Computing and Communications (PerCom), 2017 IEEE International Conference on. IEEE, 2017, pp. 190--196.
[54]
S. Seneviratne, Y. Hu, T. Nguyen, G. Lan, S. Khalifa, K. Thilakarathna, M. Hassan, and A. Seneviratne, "A survey of wearable devices and challenges," IEEE Communications Surveys & Tutorials, vol. 19, no. 4, pp. 2573--2620, 2017.
[55]
L. Shi, J. Yuan, S. Yu, and M. Li, "Ask-ban: authenticated secret key extraction utilizing channel characteristics for body area networks," in Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks. ACM, 2013, pp. 155--166.
[56]
F. Stajano, "The resurrecting duckling," in International workshop on security protocols. Springer, 1999, pp. 183--194.
[57]
K. K. Venkatasubramanian, A. Banerjee, and S. K. S. Gupta, "Pska: Usable and secure key agreement scheme for body area networks," IEEE Transactions on Information Technology in Biomedicine, vol. 14, no. 1, pp. 60--68, 2010.
[58]
E. Vildjiounaite, S.-M. Mäkelä, M. Lindholm, R. Riihimäki, V. Kyllönen, J. Mäntyjärvi, and H. Ailisto, "Unobtrusive multimodal biometrics for ensuring privacy and information security with personal devices," in International Conference on Pervasive Computing. Springer, 2006, pp. 187--201.
[59]
T. Von Buren, P. D. Mitcheson, T. C. Green, E. M. Yeatman, A. S. Holmes, and G. Troster, "Optimization of inertial micropower generators for human walking motion," IEEE Sensors journal, vol. 6, no. 1, pp. 28--38, 2006.
[60]
J. P. Walters, Z. Liang, W. Shi, and V. Chaudhary, "Wireless sensor network security: A survey," Security in distributed, grid, mobile, and pervasive computing, vol. 1, p. 367, 2007.
[61]
W. Wang, M. J. Wainwright, and K. Ramchandran, "Information-theoretic limits on sparse signal recovery: Dense versus sparse measurement matrices," IEEE Transactions on Information Theory, vol. 56, no. 6, pp. 2967--2979, 2010.
[62]
Y. Wang, G. Attebury, and B. Ramamurthy, "A survey of security issues in wireless sensor networks," 2006.
[63]
W. Xi, C. Qian, J. Han, K. Zhao, S. Zhong, X.-Y. Li, and J. Zhao, "Instant and robust authentication and key agreement among mobile devices," in Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. ACM, 2016, pp. 616--627.
[64]
T. Xiang, Z. Chi, F. Li, J. Luo, L. Tang, L. Zhao, and Y. Yang, "Powering indoor sensing with airflows: a trinity of energy harvesting, synchronous duty-cycling, and sensing," in Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems. ACM, 2013, p. 16.
[65]
L. Xie and M. Cai, "Human motion: Sustainable power for wearable electronics," IEEE Pervasive Computing, vol. 13, no. 4, pp. 42--49, 2014.
[66]
F. Xu, Z. Qin, C. C. Tan, B. Wang, and Q. Li, "Imdguard: Securing implantable medical devices with the external wearable guardian," in INFOCOM, 2011 Proceedings IEEE. IEEE, 2011, pp. 1862--1870.
[67]
W. Xu, C. Javali, G. Revadigar, C. Luo, N. Bergmann, and W. Hu, "Gait-key: A gait-based shared secret key generation protocol for wearable devices," ACM Transactions on Sensor Networks (TOSN), vol. 13, no. 1, p. 6, 2017.
[68]
W. Xu, G. Lan, Q. Lin, S. Khalifa, M. Hassan, N. Bergmann, and W. Hu, "Keh-gait: Using kinetic energy harvesting for gait-based user authentication systems," IEEE Transactions on Mobile Computing, vol. 18, no. 1, pp. 139--152, 2018.
[69]
L. Yang, W. Wang, and Q. Zhang, "Secret from muscle: Enabling secure pairing with electromyography." in SenSys, 2016, pp. 28--41.
[70]
G. Ye, Z. Tang, D. Fang, X. Chen, K. I. Kim, B. Taylor, and Z. Wang, "Cracking android pattern lock in five attempts," in The Network and Distributed System Security Symposium, 2017.
[71]
J. Yun, S. N. Patel, M. S. Reynolds, and G. D. Abowd, "Design and performance of an optimal inertial power harvester for human-powered devices," IEEE Transactions on Mobile Computing, vol. 10, no. 5, pp. 669--683, 2011.
[72]
K. Zeng, D. Wu, A. Chan, and P. Mohapatra, "Exploiting multiple-antenna diversity for shared secret key generation in wireless networks," in INFOCOM, 2010 Proceedings IEEE. IEEE, 2010, pp. 1--9.
[73]
K. Zhang, L. Zhang, and M.-H. Yang, "Real-time compressive tracking," in European conference on computer vision. Springer, 2012, pp. 864--877.
[74]
J. Zhao and Z. You, "A shoe-embedded piezoelectric energy harvester for wearable sensors," Sensors, vol. 14, no. 7, pp. 12 497--12 510, 2014.

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  1. KEHKey: Kinetic Energy Harvester-based Authentication and Key Generation for Body Area Network

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      cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
      Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 4, Issue 1
      March 2020
      1006 pages
      EISSN:2474-9567
      DOI:10.1145/3388993
      Issue’s Table of Contents
      © 2020 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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      Publication History

      Published: 18 March 2020
      Published in IMWUT Volume 4, Issue 1

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      Author Tags

      1. compressive sensing
      2. continuous authentication system
      3. gait
      4. key generation system
      5. kinetic energy harvester

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