Advertisement

Malleability Resilient Concealed Data Aggregation

  • Keyur ParmarEmail author
  • Devesh C. JinwalaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8846)

Abstract

Concealed data aggregation protects against passive attackers and ensures privacy of sensor readings at intermediate nodes. However, the use of inherently malleable privacy homomorphism makes it susceptible to active attackers. In addition, it is a well-known fact that encrypted data processing is vulnerable to pollution attacks where a single malicious node can flood the network by fake readings. Hence, there exists a need to authenticate the processed readings. Traditional authentication mechanisms are not viable due to the conflicting requirements like in-network processing and encrypted data processing. The need for en route aggregation of sensor readings, the need for encrypted data processing and the need for message authentication both at the base station and at aggregator nodes, make message authentication a formidable challenge. Homomorphic Message Authentication Codes (H-MACs) help to verify the integrity of processed sensor readings. However, the need to verify the integrity of sensor readings both at intermediate node(s) and at the base station cannot be realized simultaneously through the currently available techniques. In this paper, we combine the benefits of privacy homomorphism and H-MACs to provide malleability resilient concealed data aggregation in the presence of both insider and outsider adversaries. As per our knowledge, our solution is the first to achieve integrity protecting concealed data aggregation in the presence of both insider and outsider adversaries.

Keywords

Wireless sensor networks Concealed data aggregation Privacy homomorphism Homomorphic MAC Malleability resilience 

Notes

Acknowledgments

This research was a part of a project “A Secure Data Aggregation System and An Intrusion Detection System for Wireless Sensor Networks”. It was supported by the Department of Electronics and Information Technology, Ministry of Communications and Information Technology, Government of India.

References

  1. 1.
    Adler, J., Dai, W., Green, R., Neff, C.: Computational details of the votehere homomorphic election system. In: VoteHere. Inc. (2000)Google Scholar
  2. 2.
    Agrawal, S., Boneh, D.: Homomorphic MACs: MAC-Based Integrity for Network Coding. In: Abdalla, M., Pointcheval, D., Fouque, P.-A., Vergnaud, D. (eds.) ACNS 2009. LNCS, vol. 5536, pp. 292–305. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. 3.
    Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Comput. Netw.: Int. J. Comput. Telecommun. Netw. 38, 393–422 (2002)CrossRefGoogle Scholar
  4. 4.
    Apavatjrut, A., Znaidi, W., Fraboulet, A., Goursaud, C., Lauradoux, C., Minier, M.: Energy friendly integrity for network coding in wireless sensor networks. In: Proceedings of the 2010 Fourth International Conference on Network and System Security. pp. 223–230. NSS ’10, IEEE Computer Society, Washington, DC, USA (2010)Google Scholar
  5. 5.
    Castelluccia, C., Chan, A.C.F., Mykletun, E., Tsudik, G.: Efficient and provably secure aggregation of encrypted data in wireless sensor networks. ACM Trans. Sens. Netw. (TOSN) 5(3), 20:1–20:36 (2009)Google Scholar
  6. 6.
    Chan, A.C.F., Castelluccia, C.: On the (im)possibility of aggregate message authentication codes. In: ISIT. pp. 235–239. IEEE (2008)Google Scholar
  7. 7.
    Domingo-Ferrer, J.: A provably secure additive and multiplicative privacy homomorphism. In: Chan, A.H., Gligor, V.D. (eds.) ISC 2002. LNCS, vol. 2433, pp. 471–483. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  8. 8.
    Fasolo, E., Rossi, M., Widmer, J., Zorzi, M.: In-network aggregation techniques for wireless sensor networks: a survey. Wireless. Commun. IEEE 14, 70–87 (2007)CrossRefGoogle Scholar
  9. 9.
    Girao, J., Westhoff, D., Schneider, M.: CDA: concealed data aggregation for reverse multicast traffic in wireless sensor networks. In: 40th International Conference on Communications, IEEE ICC 2005 pp. 3044–3049 (May 2005)Google Scholar
  10. 10.
    Gura, N., Patel, A., Wander, A., Eberle, H., Shantz, S.C.: Comparing Elliptic Curve Cryptography and RSA on 8-bit CPUs. In: Joye, M., Quisquater, J.-J. (eds.) CHES 2004. LNCS, vol. 3156, pp. 119–132. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  11. 11.
    Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., Pister, K.: System architecture directions for networked sensors. ACM. SIGPLAN. Not. 35(11), 93–104 (2000)CrossRefGoogle Scholar
  12. 12.
    Hoffstein, J., Pipher, J., Silverman, J.: An Introduction to Mathematical Cryptography, 1st edn., New York, Incorporated (2008)zbMATHGoogle Scholar
  13. 13.
    Karlof, C., Sastry, N., Wagner, D.: Tinysec: A link layer security architecture for wireless sensor networks. In: Proceedings of the 2Nd International Conference on Embedded Networked Sensor Systems pp. 162–175. SenSys ’04, ACM, New York, (2004)Google Scholar
  14. 14.
    Koblitz, N.: Elliptic curve cryptosystems. Math. Comput. 48(177), 203–209 (1987)CrossRefMathSciNetzbMATHGoogle Scholar
  15. 15.
    Malan, D.J., Welsh, M., Smith, M.D.: A public-key infrastructure for key distribution in tinyos based on elliptic curve cryptography. In: First IEEE International Conference on Sensor and Ad Hoc Communications and Network (IEEE SECON 2004), pp. 71–80 (Oct 2004)Google Scholar
  16. 16.
    Mykletun, E., Girao, J., Westhoff, D.: Public key based cryptoschemes for data concealment in wireless sensor networks. In: IEEE International Conference on Communications. ICC-2006, Istanbul, Turkey (June 2006)Google Scholar
  17. 17.
    Okamoto, T., Uchiyama, S.: A New Public-Key Cryptosystem as Secure as Factoring. In: Nyberg, K. (ed.) EUROCRYPT 1998. LNCS, vol. 1403, pp. 308–318. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  18. 18.
    Rivest, R., Adleman, L., Dertouzos, M.: On data banks and privacy homomorphisms. In: Foundations of Secure Computation, pp. 169–177 (1978)Google Scholar
  19. 19.
    Ugus, O.: Asymmetric Homomorphic Encryption Transformation for Securing Distributed Data Storage in Wireless Sensor Networks (in cooperation with NEC Heidelberg). Master’s thesis, Technische Universität Darmstadt (2007)Google Scholar
  20. 20.
    Westhoff, D., Girao, J., Acharya, M.: Concealed data aggregation for reverse multicast traffic in sensor networks: encryption, key distribution, and routing adaptation. IEEE. Trans. Mob. Comput. 5(10), 1417–1431 (2006)CrossRefGoogle Scholar
  21. 21.
    Westhoff, D., Ugus, O.: Malleability resilient (premium) concealed data aggregation. In: Proceedings of the 4th IEEE International Workshop on Data Security and Privacy in Wireless Networks (D-SPAN’13). IEEE Press, Madrid Spain (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.S. V. National Institute of TechnologySuratIndia

Personalised recommendations