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A sensitive data aggregation scheme for body sensor networks based on data hiding

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Abstract

Body sensor networks (BSNs) enable the pervasive, long-term, and real-time monitoring in any environment and without restriction of activity. Security and privacy are extremely critical issues of BSNs, as sensitive information is transmitted through the wireless network. This paper proposes a novel sensitive data aggregation scheme based on data hiding for BSNs, namely SDAS. SDAS adopts the packet combination based on the sensitive data aggregation tree built in each BSN to reduce the transmission energy consumption by eliminating transmitted redundancy. After lossless compression, the compressed sensitive data are embedded into various ordinary data in the combined packet by using a lightweight data hiding algorithm to prevent the disclosure of the sensitive data and avoid arousing the attention of attackers. Extensive analysis demonstrates that our proposed scheme can ensure a high level of security and privacy of the sensitive data without affecting the ordinary data quality, while delivering low power consumption.

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References

  1. Jovanov E, Poon CC, Yang GZ, Zhang YT (2009) Guest editorial body sensor networks: from theory to emerging applications. IEEE Trans Inf Technol Biomed 13(6):859–863. doi:10.1109/TITB.2009.2034564

    Article  Google Scholar 

  2. Hanson MA, Powell HC, Barth AT, Ringgenberg K, Calhoun JH, Aylor Lach J (2009) Body area sensor networks: challenges and opportunities. Computer 42(1):58–65. doi:10.1109/MC.2009.5

    Article  Google Scholar 

  3. Lim S, Oh TH, Choi YB, Lakshman T (2010) Security issues on wireless body area network for remote healthcare monitoring. 2010 IEEE international conference on sensor networks, ubiquitous, and trustworthy computing, Newport Beach, California, USA, June 7–9, pp 327–332. doi:10.1109/SUTC.2010.61

  4. Ameen M Al, Liu J, Kwak K (2010) Security and privacy issues in wireless sensor networks for healthcare applications. J Med Syst. doi:10.1007/s10916-010-9449-4

  5. Nosowsky R, Giordano TJ (2006) The Health Insurance Portability and Accountability Act of 1996 (HIPAA) privacy rule: implications for clinical research. Annu Rev Med 57:575–590. doi:10.1146/annurev.med.57.121304.131257

    Article  Google Scholar 

  6. Xiao X, Sun X, Yang L, Chen M (2007) Secure data transmission of wireless sensor network based on information hiding. Fourth annual international conference on mobile and ubiquitous systems: networking & services (MobiQuitous 2007), Philadelphia, PA, USA, August 6–10, 1–6, 2007. doi:10.1109/MOBIQ.2007.4451044

  7. Yang J, Sun X, Wang B, Xiao X, Wang X, Luo D (2010) Bloom filter-based data hiding algorithm in wireless sensor networks. 5th international conference on future information technology (FutureTech), Busan, Korea, May 20–24, 1–6, 2010. doi:10.1109/FUTURETECH.2010.5482761

  8. Bista R, Chang JW (2010) Privacy-preserving data aggregation protocols for wireless sensor networks: a survey. Sensors 10(5):4577–4601. doi:10.3390/s100504577

    Article  Google Scholar 

  9. Rathod VJ, Mehta M (2011) Security in wireless sensor network: a survey. Ganpat Univ J Eng Technol 1(1):35–44

    Google Scholar 

  10. Taban G, Gligor VD (2009) Privacy-preserving integrity-assured data aggregation in sensor networks In: Proceeding of international symposium on secure computing (SecureCom), Vancouver, Canada, August 29–31, 168–175, 2009. doi:10.1109/CSE.2009.389

  11. Chan ACF, Castelluccia C (2011) A security framework for privacy-preserving data aggregation in wireless sensor networks. ACM Trans Sensor Netw (TOSN) 7(4):29–73. doi:10.1145/1921621.1921623

    Google Scholar 

  12. Ponomarchuk Y, Seo D-W (2010) Intrusion detection based on traffic analysis and fuzzy inference system in wireless sensor networks. J Conver 1(1):35–42

    Google Scholar 

  13. Xie B, Kumar A, Zhao D, Reddy R, He B (2010) On secure communication in integrated heterogeneous wireless networks. Int J Inform Technol Commun Converg 1(1):4–23

    Article  Google Scholar 

  14. Wang S-J, Tsai Y-R, Shen C-C, Chen P-Y (2010) Hierarchical key derivation scheme for group-oriented communication systems. Int J Inform Technol Commun Converg 1(1):66–76

    Article  Google Scholar 

  15. Sarkar P, Saha A (2011) Security enhanced communication in wireless sensor networks using reed-muller codes and partially balanced incomplete block designs. J Converg 2(1):23–30

    Google Scholar 

  16. Acharya D, Kumar V (2010) A secure pervasive health care system using location dependent unicast key generation scheme. In: Proceedings of the 3rd workshop on Ph. D. students in information and knowledge management, Toronto, ON, Canada, October 26–30, pp 87–90, 2010. doi:10.1145/1871902.1871919

  17. Mana M, Feham M, Bensaber BA (2011) Trust key management scheme for wireless body area networks. Int J Netw Secur 12(2):75–83. doi:ijns-2011-v12-n2-p84-91

    Google Scholar 

  18. Lin X, Lu R, Shen X, Nemoto Y, Kato N (2009) SAGE: a strong privacy-preserving scheme against global eavesdropping for ehealth systems. IEEE J Sel Areas Commun 27(4):365–378. doi:10.1109/JSAC.2009.090502

    Article  Google Scholar 

  19. Tan CC, Wang H, Zhong S, Li Q (2009) IBE-lite: a lightweight identity-based cryptography for body sensor networks. IEEE Trans Inf Technol Biomed 13(6):926–932. doi:10.1109/TITB.2009.2033055

    Article  Google Scholar 

  20. Miao F, Jiang L, Li Y, Zhang YT (2009) Biometrics based novel key distribution solution for body sensor networks. Annual international conference of the IEEE engineering in medicine and biology society (EMBC 2009), Minneapolis, MN, USA, September 2–6, pp 2458–2461, 2009. doi:10.1109/IEMBS.2009.5334698

  21. Li M, Yu S, Lou W, Ren K (2010) Group device pairing based secure sensor association and key management for body area networks. In: Proceedings IEEE INFOCOM, San Diego, CA, USA, March 4–19, 1–9, 2010. doi:10.1109/INFCOM.2010.5462095

  22. Venkatasubramanian KK, Gupta SKS (2010) Physiological value-based efficient usable security solutions for body sensor networks. ACM Trans Sens Netw (TOSN) 6(4):1–36. doi:10.1145/1777406.1777410

    Article  Google Scholar 

  23. Eldefrawy MH, Khan MK, Alghathbar K, Tolba AS, Kim KJ (2011) Authenticated key agreement with rekeying for secured body sensor networks. Sensors 11(6):5835–5849. doi:10.3390/s110605835

    Article  Google Scholar 

  24. Sun JZ (2007) Using packet combination in multi-query optimization for data collection in sensor networks. Mobile Ad-Hoc Sens Netw 4864:645–656. doi:10.1007/978-3-540-77024-4_59

    Article  Google Scholar 

  25. Kimura N, Latifi S (2005) A survey on data compression in wireless sensor networks. International conference on information technology: coding and computing (ITCC 2005), Las Vegas, Nevada, USA, April 4–6, 8–13, 2005. doi:10.1109/ITCC.2005.43

  26. Hill J, Szewczyk R, Woo A, Hollar S, Culler D, Pister K (2000) System architecture directions for networked sensors. Acm Sigplan Notices 35(11):93–104. doi:10.1145/356989.356998

    Article  Google Scholar 

  27. Pham HN, Pediaditakis D, Boulis A (2007) From simulation to real deployments in wsn and back. IEEE international symposium on a world of wireless, mobile and multimedia networks (WoWMoM2007), Helsinki, Finland, June 18–21, 1–6, 2007. doi:10.1109/WOWMOM.2007.4351800

  28. Ichimaru Y, Moody GB (1999) Development of the polysomnographic database on CD-ROM. Psychiatry Clin Neurosci 53(2):175–177. doi:10.1046/j.1440-1819.1999.00527.x

    Article  Google Scholar 

  29. Varga A (2001) The OMNeT++ discrete event simulation system. In: Proceedings of the European simulation Multicon ference (ESM2001), Prague, Czech Republic, June 6–9, pp 319–324

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Acknowledgments

This work was partially supported by the National Natural Science Foundation of China under Grant No. 61173179, No. 60903153, and the Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. School of Software, Dalian University of Technology, Dalian, 116620, China

    Jiankang Ren, Guowei Wu & Lin Yao

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  1. Jiankang Ren
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  2. Guowei Wu
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  3. Lin Yao
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Correspondence to Guowei Wu.

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Ren, J., Wu, G. & Yao, L. A sensitive data aggregation scheme for body sensor networks based on data hiding. Pers Ubiquit Comput 17, 1317–1329 (2013). https://doi.org/10.1007/s00779-012-0566-6

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  • DOI: https://doi.org/10.1007/s00779-012-0566-6

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