research-article

Securing data provenance in body area networks using lightweight wireless link fingerprints

Authors:

Vijay Sivaraman,

Diethelm Ostry,

Sanjay JhaAuthors Info & Claims

TrustED '13: Proceedings of the 3rd international workshop on Trustworthy embedded devices

Pages 65 - 72

https://doi.org/10.1145/2517300.2517303

Published: 04 November 2013 Publication History

Abstract

Wireless bodyworn sensing devices are becoming popular for fitness, sports training and personalized healthcare applications. Securing the data generated by these devices is essential if they are to be integrated into the current health infrastructure and employed in medical applications. In this paper, we propose a mechanism to secure data provenance for these devices by exploiting symmetric spatio-temporal characteristics of the wireless link between two communicating parties. Our solution enables both parties to generate closely matching 'link' fingerprints which uniquely associate a data session with a wireless link such that a third party, at a later date, can verify the links the data was communicated on. These fingerprints are very hard for an eavesdropper to forge, lightweight compared to traditional provenance mechanisms, and allow for interesting security properties such as accountability and non-repudiation. We validate our solution with experiments using bodyworn devices in scenarios approximating actual device deployment, and we present optimization mechanisms. We believe this is a promising first step towards using wireless-link characteristics for data provenance in body area networks.

References

[1]

Nike+ FuelBand. Retrieved on 21 July, 2013. http://www.nike.com/us/en_us/c/nikeplus-fuelband.

[2]

Fitbit Flex. Retrieved on 21 July, 2013. http://allthingsd.com/20130715/fitbit-flex-vs- jawbone-up-and-more-a-wearables-comparison/.

[3]

Toumaz Technology Ltd. Sensium Life Platform. http://www.toumaz.com/page.php?page=sensium_intro.

[4]

David Szondy. Bracelet Uses Social Network to Protect Civil Rights Activists. 7 April, 2013. http://goo.gl/MIEk2.

[5]

Waiting for Apple's iWatch. 22 March, 2013. http://goo.gl/xTsQO.

[6]

Disposable Wireless Sensor Market Shows Signs of Life: Healthcare Shipments to Reach 5 Million in 2018. 3 March, 2013. http://goo.gl/V9QoP0.

[7]

A. S. Wander, N. Gura, H. Eberle, V. Gupta, and S. C. Shantz. Energy Analysis of Public-key Cryptography for Wireless Sensor Networks. In 3rd IEEE International Conference on Pervasive Computing and Communications (PerCom), pages 324--328, 2005.

Digital Library

[8]

U. Braun, A. Shinnar, and M. I. Seltzer. Securing Provenance. In USENIX Summit on Hot Topics in Security (HotSec), 2008.

Digital Library

[9]

D. J. Pohly, S. McLaughlin, P. McDaniel, and K. Butler. Hi-Fi: Collecting High-fidelity Whole-system Provenance. In Proceedings of the 28th ACM Annual Computer Security Applications Conference, pages 259--268, 2012.

Digital Library

[10]

B. Przydatek, D. Song, and A. Perrig. SIA: Secure Information Aggregation in Sensor Networks. In Proceedings of the 1st ACM International Conference on Embedded Networked Sensor Systems, pages 255--265, 2003.

Digital Library

[11]

H. Lim, Y. Moon, and E. Bertino. Provenance-based Trustworthiness Assessment in Sensor Networks. In Proceedings of the Seventh ACM International Workshop on Data Management for Sensor Networks, pages 2--7, 2010.

Digital Library

[12]

H. Lim, G. Ghinita, E. Bertino, and M. Kantarcioglu. A Game-Theoretic Approach for High-Assurance of Data Trustworthiness in Sensor Networks. In 28th IEEE International Conference on Data Engineering (ICDE), pages 1192--1203, 2012.

Digital Library

[13]

M. A. Chowdhury, W. Mciver, and J. Light. Data Association in Remote Health Monitoring Systems. IEEE Communications Magazine, 50(6):144--149, 2012.

[14]

S. T. Ali, V. Sivaraman, and D. Ostry. Authentication of Lossy Data in Body-sensor Networks for Healthcare Monitoring. In 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), pages 470--478, 2012.

[15]

J. C. Sriram, M. Shin, T. Choudhury, and D. Kotz. Activity-aware ECG-based Patient Authentication for Remote Health Monitoring. In Proceedings of the ACM International Conference on Multimodal Interfaces, pages 297--304, 2009.

Digital Library

[16]

K. B. Rasmussen and S. Capkun. Implications of Radio Fingerprinting on the Security of Sensor Networks. In Third International Conference on Security and Privacy in Communications Networks, SecureComm, pages 331--340. IEEE, 2007.

[17]

B. Shebaro, S. Sultana, S. R. Gopavaram, and E. Bertino. Demonstrating a Lightweight Data Provenance for Sensor Networks. In Proceedings of the ACM Conference on Computer and Communications Security, pages 1022--1024, 2012.

Digital Library

[18]

M. G. Zapata. Secure Ad hoc On-demand Distance Vector Routing. ACM SIGMOBILE Mob. Comput. Commun. Rev., 6(3):106--107, 2002.

Digital Library

[19]

S. Jana, S. N. Premnath, M. Clark, S. K. Kasera, N. Patwari, and S. V. Krishnamurthy. On the Effectiveness of Secret Key Extraction from Wireless Signal Strength in Real Environments. In Proceedings of the 15th ACM Annual International Conference on Mobile Computing and Networking, pages 321--332, 2009.

Digital Library

[20]

Z. Li, W. Xu, R. Miller, and W. Trappe. Securing Wireless Systems via Lower Layer Enforcements. In Proceedings of the 5th ACM Workshop on Wireless Security, pages 33--42, 2006.

Digital Library

[21]

J. Tang and P. Fan. A RSSI-based Cooperative Anomaly Detection Scheme for Wireless Sensor Networks. In International Conference on Wireless Communications, WiCom, pages 2783--2786. IEEE, 2007.

[22]

N. Patwari and S. K. Kasera. Robust Location Distinction using Temporal Link Signatures. In Proceedings of the 13th Annual ACM International Conference on Mobile Computing and Networking, pages 111--122, 2007.

Digital Library

[23]

S. T. Ali, V. Sivaraman, and D. Ostry. Zero Reconciliation Secret Key Generation for Body-worn Health Monitoring Devices. In Proceedings of the 5th ACM Conference on Security and Privacy in Wireless and Mobile Networks, pages 39--50, 2012.

Digital Library

[24]

L. Shi, M. Li, S. Yu, and J. Yuan. Bana: Body Area Network Authentication Exploiting Channel Characteristics. In Proceedings of the 5th ACM conference on Security and Privacy in Wireless and Mobile Networks, pages 27--38, 2012.

Digital Library

[25]

W. C. Jakes. Microwave Mobile Communications. Wiley, 1974.

Digital Library

[26]

S. Mathur, W. Trappe, N. Mandayam, C. Ye, and A. Reznik. Radio-telepathy: Extracting a Secret Key from an Unauthenticated Wireless Channel. In Proceedings of the 14th ACM International Conference on Mobile Computing and Networking, pages 128--139, 2008.

Digital Library

[27]

L. Yao, S. T. Ali, V. Sivaraman, and D. Ostry. Improving Secret Key Generation Performance for On-body Devices. In Proceedings of the 6th International Conference on Body Area Networks, pages 19--22. ICST, 2011.

Digital Library

[28]

D. Culler, D. Estrin, and M. Srivastava. Guest editors' introduction: Overview of sensor networks. Computer, 37:41--49, 2004.

Digital Library

[29]

NIST. A Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications, 2001.

Cited By

Sathio ABrohi A(2021)The Imperative Role of Pervasive Data in HealthcarePervasive Healthcare10.1007/978-3-030-77746-3_2(17-29)Online publication date: 16-Nov-2021
https://doi.org/10.1007/978-3-030-77746-3_2
Shakiba-Herfeh MChorti AVincent Poor H(2021)Physical Layer Security: Authentication, Integrity, and ConfidentialityPhysical Layer Security10.1007/978-3-030-55366-1_6(129-150)Online publication date: 25-Jan-2021
https://doi.org/10.1007/978-3-030-55366-1_6
Siddiqi MAli SSivaraman V(2020)Forensic Verification of Health Data From Wearable Devices Using Anonymous WitnessesIEEE Internet of Things Journal10.1109/JIOT.2020.29829587:11(10745-10762)Online publication date: Nov-2020
https://doi.org/10.1109/JIOT.2020.2982958
Show More Cited By

Index Terms

Securing data provenance in body area networks using lightweight wireless link fingerprints
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language features
        Data types and structures

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Published In

cover image ACM Conferences

TrustED '13: Proceedings of the 3rd international workshop on Trustworthy embedded devices

November 2013

82 pages

ISBN:9781450324861

DOI:10.1145/2517300

General Chair:
Ahmad-Reza Sadeghi
TU-Darmstadt & Fraunhofer SIT & Intel ICRI-SC, Germany
,
Program Chairs:
Frederik Armknecht
University of Mannheim, Germany
,
Jean-Pierre Seifert
TU Berlin & Deutsche Telekom Laboratories, Germany

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSAC: ACM Special Interest Group on Security, Audit, and Control

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 November 2013

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Research-article

Conference

CCS'13

Sponsor:

SIGSAC

CCS'13: 2013 ACM SIGSAC Conference on Computer and Communications Security

November 4, 2013

Berlin, Germany

Acceptance Rates

TrustED '13 Paper Acceptance Rate 7 of 14 submissions, 50%;

Overall Acceptance Rate 24 of 49 submissions, 49%

Upcoming Conference

CCS '25

Sponsor:
sigsac

ACM SIGSAC Conference on Computer and Communications Security

October 13 - 17, 2025

Taipei , Taiwan

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Cited By

Sathio ABrohi A(2021)The Imperative Role of Pervasive Data in HealthcarePervasive Healthcare10.1007/978-3-030-77746-3_2(17-29)Online publication date: 16-Nov-2021
https://doi.org/10.1007/978-3-030-77746-3_2
Shakiba-Herfeh MChorti AVincent Poor H(2021)Physical Layer Security: Authentication, Integrity, and ConfidentialityPhysical Layer Security10.1007/978-3-030-55366-1_6(129-150)Online publication date: 25-Jan-2021
https://doi.org/10.1007/978-3-030-55366-1_6
Siddiqi MAli SSivaraman V(2020)Forensic Verification of Health Data From Wearable Devices Using Anonymous WitnessesIEEE Internet of Things Journal10.1109/JIOT.2020.29829587:11(10745-10762)Online publication date: Nov-2020
https://doi.org/10.1109/JIOT.2020.2982958
Aman MChua KSikdar B(2019)Hardware Primitives-Based Security Protocols for the Internet of ThingsCryptographic Security Solutions for the Internet of Things10.4018/978-1-5225-5742-5.ch005(117-141)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-5742-5.ch005
Nikiforov DKonev AAntonov MShelupanov A(2019)Structure of information security subsystem in the systems of commercial energy resources accountingJournal of Physics: Conference Series10.1088/1742-6596/1145/1/0120181145(012018)Online publication date: 9-Jan-2019
https://doi.org/10.1088/1742-6596/1145/1/012018
Zafar FKhan ASuhail SAhmed IHameed KKhan HJabeen FAnjum A(2018)Trustworthy dataJournal of Network and Computer Applications10.1016/j.jnca.2017.06.00394:C(50-68)Online publication date: 28-Dec-2018
https://dl.acm.org/doi/10.1016/j.jnca.2017.06.003
Aman MChua KSikdar BChow RSaldamli G(2017)Secure Data Provenance for the Internet of ThingsProceedings of the 3rd ACM International Workshop on IoT Privacy, Trust, and Security10.1145/3055245.3055255(11-14)Online publication date: 2-Apr-2017
https://dl.acm.org/doi/10.1145/3055245.3055255

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