Abstract
As illustrated in Chap. 3, the most recent research on human associated DTNs uses social information to improve performance, thus demonstrating social characteristics are important factors to improve performance. However, little has been done concerning the privacy issue in DTNs. With increasing use of social information, more and more social characteristics related data is disclosed without permission. Due to the privacy issue, most trace providers do not want to release data with meaningful social information, that may be used to identify the data entered especially for a large dataset. For example, AOL published a query logs but quickly removed it due to the re-identification issues addressed in [1]. Consequently, researchers are trying to find ways to anonymize personal information while maintaining network functioning.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barbaro, M., Zeller, T.: A face is exposed for AOL searcher no. 4417749. New York Times 9(2008) (2006)
Bayardo, R., Agrawal, R.: Data privacy through optimal k-anonymization. In: Proceedings of IEEE ICDE, Tokyo, pp. 217–228. IEEE (2005)
Lu, R., Li, X., Luan, T.H., Liang, X., Shen, X.: Pseudonym changing at social spots: an effective strategy for location privacy in VANETs. IEEE Trans. Veh. Technol. 61(1), 86–96 (2012)
Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertain. Fuzziness Knowledgebased Syst. 10(5), 557–570 (2002)
Liang, X., Zhang, K., Shen, X., Lin, X.: Security and privacy in mobile social networks: challenges and solutions. IEEE Wirel. Commun. 21(1), 33–41 (2014)
Samarati, P.: Protecting respondents identities in microdata release. IEEE Trans. Knowledge Data Eng. 13, 1010–1027 (2001)
Wang, K., Xu, Y., Fu, A.-C., Wong, R.-W.: FF-anonymity: when quasi-identifiers are missing. In: Proceedings of IEEE ICDE, Shanghai, pp. 1136–1139 (2009)
Sweney, L.: Achieving k-anonymity privacy protection using generalization and suppression. Int. J. Uncertain. Fuzziness Knowledge-Based Syst. 10(5), 571–588 (2002)
Iyengar, V.S.: Transforming data to satisfy privacy constraints. In: Proceedings of ACM SIGKDD, Edmonton, pp. 279–288, ACM, New York (2002)
Sweeney, L.: Datafly: a system for providing anonymity in medical data. In: Proceedings of IFIP TC11 WG11.3 Eleventh International Conference on Database Security XI: Status and Prospects, pp. 356–381. Chapman & Hall, London, Lake Tahoe, California (1998)
Harary, F.: Graph Theory. Addison Wesley, Reading (1969)
Alvarez-Hamelin, J.I., Dall’Asta, L., Barrat, A., Vespignani, A.: k-core decomposition: a tool for the visualization of large scale networks. CoRR, abs/cs/0504107 (2005)
Batagelj, V., Zaversnik, M.: Generalized cores. CoRR, cs.DS/0202039 (2002)
Myers, C.R.: Software systems as complex networks: structure, function, and evolvability of software collaboration graphs. Phys. Rev. E 68, 046116 (2003)
Gao, L., Li, M., Zhu, T., Bonti, A., Zhou, W., Yu, S.: AMDD: exploring entropy based anonymous multi-dimensional data detection for network optimization in human associated DTNs. In: Proceedings of IEEE TrustCom, Liverpool, pp. 1245–1250 (2012)
Shannon, C.E.: A mathematical theory of communication. Bell Syst. Tech. J. 27(3), 379–423 (1948)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2015 The Author(s)
About this chapter
Cite this chapter
Gao, L., Yu, S., Luan, T.H., Zhou, W. (2015). Privacy Protected Routing in Delay Tolerant Networks. In: Delay Tolerant Networks. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-18108-0_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-18108-0_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-18107-3
Online ISBN: 978-3-319-18108-0
eBook Packages: Computer ScienceComputer Science (R0)