Abstract
Targeted Mobile Advertising (TMA) has emerged as a significant driver of the Internet economy. TMA gives rise to interesting challenges: there is a need to balance privacy and utility; there is a need to guarantee that applications’ access to resources is appropriate; and there is a need to ensure that the targeting of ads is effective. As many authors have argued, formal models are ideal vehicles for reasoning about privacy, as well as for reasoning about the relationship between privacy and utility. To this end, we describe how the formal notation Z has been used to develop formal models to underpin a prototype privacy-preserving TMA system. We give consideration to how formal models can help in underpinning the prototype system, in analysing privacy in the context of targeted mobile advertising, and in allowing users to specify control of their personal information.
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
Abe, A., Simpson, A.C.: Formal models for privacy. In: Proceedings of the 9th International Workshop on Privacy and Anonymity in the Information Society (PAIS 2016). Bordeaux, France (2016)
Ahn, H., Kim, K.J., Han, I.: Mobile advertisement recommender system using collaborative filtering: MAR-CF. In: Proceedings of the 2006 Conference of the Korea Society of Management Information Systems, pp. 709–715. The Korea Society of Management Information Systems (2006)
Beales, H.: The value of behavioral targeting (2010). http://www.networkadvertising.org/pdfs/Beales_NAI_Study.pdf Accessed April 2015
Farahat, A.: Privacy preserving frequency capping in Internet banner advertising. In: Proceedings of the 18th International Conference on World Wide Web (WWW 2009), pp. 1147–1148. ACM, Madrid, Spain (2009)
Goldfarb, A., Tucker, C.E.: Privacy regulation and online advertising. Manag. Sci. 57(1), 57–71 (2011)
Guha, S., Cheng, B., Francis, P.: Privad: Practical privacy in online advertising. In: Proceedings of the 8th USENIX Conference on Networked Systems Design and Implementation (NSDI 2011), pp. 169–182. Boston, MA, USA (2011)
Haddadi, H.: Fighting online click-fraud using bluff ads. ACM SIGCOMM Comput. Commun. Rev. 40(2), 21–25 (2010)
Haddadi, H., Hui, P., Brown, I.: MobiAd: Private and scalable mobile advertising. In: Proceedings of the 5th ACM International Workshop on Mobility in the Evolving Internet Architecture (MobiArch 2010), pp. 33–38. ACM, Chicago, IL, USA (2010)
Hardt, M., Nath, S.: Privacy-aware personalization for mobile advertising. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security (CCS 2012), pp. 662–673. ACM, Raleigh, NC, USA (2012)
ISO/IEC: ISO/IEC 13658: Information Technology – Z Formal Specification Notation – Syntax, Type System and Semantics. ISO/IEC (2002)
Jacky, J.: Model-based testing with spec#. In: Davies, J., Schulte, W., Barnett, M. (eds.) ICFEM 2004. LNCS, vol. 3308, pp. 5–6. Springer, Heidelberg (2004)
Liu, Y., Simpson, A.C.: Privacy-preserving targeted mobile advertising: Requirements, design, and a prototype implementation. Software: Practice and Experience (2016). http://dx.doi.org/10.1002/spe.2403
Plagge, D., Leuschel, M.: Validating Z specifications using the ProB animator and model checker. In: Davies, J., Gibbons, J. (eds.) IFM 2007. LNCS, vol. 4591, pp. 480–500. Springer, Heidelberg (2007)
Roesner, F., Kohno, T., Moshchuk, A., Parno, B., Wang, H.J., Cowan, C.: User-driven access control: Rethinking permission granting in modern operating systems. In: Proceedings of the 2012 IEEE Symposium on Security and privacy (SP 2012), pp. 224–238. IEEE, San Francisco, CA, USA (2012)
Toubiana, V., Narayanan, A., Boneh, D., Nissenbaum, H., Barocas, S.: Adnostic: Privacy preserving targeted advertising. In: Proceedings of the 17th Annual Network and Distributed System Security Symposium (NDSS 2010). San Diego, CA, USA (2010), April 6, 2016. https://www.isoc.org/isoc/conferences/ndss/10/pdf/05.pdf
Tschantz, M.C., Wing, J.M.: Formal methods for privacy. In: Cavalcanti, A., Dams, D.R. (eds.) FM 2009. LNCS, vol. 5850, pp. 1–15. Springer, Heidelberg (2009)
Yan, J., Liu, N., Wang, G., Zhang, W., Jiang, Y., Chen, Z.: How much can behavioral targeting help online advertising? In: Proceedings of the 18th International Conference on World Wide Web (WWW 2009), pp. 261–270. ACM, Madrid, Spain (2009)
Yuan, S.T., Tsao, Y.W.: A recommendation mechanism for contextualized mobile advertising. Expert Syst. Appl. 24(4), 399–414 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Liu, Y., Simpson, A. (2016). Privacy-Preserving Targeted Mobile Advertising: Formal Models and Analysis. In: Livraga, G., Torra, V., Aldini, A., Martinelli, F., Suri, N. (eds) Data Privacy Management and Security Assurance. DPM QASA 2016 2016. Lecture Notes in Computer Science(), vol 9963. Springer, Cham. https://doi.org/10.1007/978-3-319-47072-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-47072-6_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-47071-9
Online ISBN: 978-3-319-47072-6
eBook Packages: Computer ScienceComputer Science (R0)