Abstract
Personalization of web applications is the complex process of dynamically rendering the application responsive to the unique needs of individual users. Nevertheless, the information required for achieving the personalization procedures is usually gathered and stored beyond the user’s control. This is a situation that raises serious privacy concerns to the end-users and may drive them to reject the application. For example, when browsing an adaptive e-commerce website, users are not aware which behavior will be monitored and logged, how it will be processed, how long it will be stored, and with whom it will be shared in the long run, thus they may hesitate to visit the website. In this chapter after an introduction to the state of the art in privacy preserving personalized web applications we present an abstract architecture that enables users to fine-tune their privacy level (and in result their personalization experience) according to the trust they put on different applications. Since the data is stored on the client side, this approach by definition enhances user privacy.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Kolias, C., Kolias, V., Anagnostopoulos, I., Kambourakis, G., Kayafas, E.: Enhancing User Privacy in Adaptive Web Sites with Client-Side User Profiles. In: Third International Workshop on Semantic Media Adaptation and Personalization, SMAP 2008, December 15-16, pp. 170–176 (2008)
Kobsa, A., Koenemann, J., Pohl, W.: Personalised hypermedia presentation techniques for improving online customer relationships. The Knowledge Engineering Review 16(2), 111–155 (2001)
Brusilovsky, P., Maybury, M.T.: From adaptive hypermedia to the adaptive web. Communications of the ACM 45(5) (May 2002)
Kobsa, A.: Personalized hypermedia and international privacy. Communications of the ACM 45(5) (May 2002)
Teltzrow, M., Kobsa, A.: Impacts of User Privacy Preferences on Personalized Systems: A Comparative Study. In: Designing Personalized User Experiences in eCommerce, pp. 315–332. Kluwer Academic (2004)
W3C, http://www.w3.org/ (accessed November 27, 2011)
W3C, A P3P Preference Exchange Language 1.0 (APPEL1.0), http://www.w3.org/TR/P3P-preferences/ (accessed November 27, 2011)
W3C, The Platform for Privacy Preferences 1.0 (P3P1.0), http://www.w3.org/TR/P3P/ (accessed November 27, 2011)
AT&T Privacy Bird, http://www.privacybird.org/ (accessed November 27, 2011)
Guha, S., Reznichenko, A., Tang, K., Haddadi, H., Francis, P.: Serving Ads from localhost for Performance, Privacy, and Profit. In: Proceedings of Hot Topics in Networking (November 2009)
Preibusch, S.: Implementing Privacy Negotiations in E-Commerce. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds.) APWeb 2006. LNCS, vol. 3841, pp. 604–615. Springer, Heidelberg (2006)
TRUSTe, http://www.truste.org/ (accessed November 27, 2011)
Bleichenbacher, D., Gabber, E., Gibbons, P.B., Matias, Y., Mayer, A.: On secure and pseudonymous client relationships with multiple servers. In: Proceedings of the 3rd USENIX Electronic Commerce Workshop, pp. 99–108 (1998)
Gabber, E., Gibbons, P., Matias, Y., Mayer, A.: How to make personalized web browsing simple, secure, and anonymous. In: Proceedings of the Conference on Financial Cryptography. Springer, New York (1997)
Kobsa, A., Schreck, J.: Privacy through pseudonymity in user-adaptive systems. ACM Transactions on Internet Technology (TOIT) 3(2), 149–183 (2003)
Finin, T., Weber, J.: Draft specification of the KQML agent-communication language. Tech. Rep. (1993), http://www.cs.umbc.edu/kqml/kqmlspec/spec.html (accessed November 27, 2011)
Ishitani, L., Almeida, V., Meira Jr., W.: Masks: Bringing Anonymity and Personalization Together. IEEE Security and Privacy 1(3), 18–23 (2003)
Samarati, P.: Protecting respondents identities in microdata release. IEEE Transactions on Knowledge and Data Engineering 13(6), 1010–1027 (2001)
Gedik, B., Liu, L.: Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms. IEEE Transactions on Mobile Computing 7(1), 1–18 (2008)
Stenneth, L., Yu, P.S., Wolfson, O.: Mobile systems location privacy: “MobiPriv” a robust k anonymous system. In: 2010 IEEE 6th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), October 11-13, pp. 54–63 (2010)
You, T., Peng, W., Lee, W.-C.: Protecting moving trajectories using dummies. In: International Workshop on Privacy-Aware Location-Based Mobile Services (2007)
Ghinita, G., Kalnis, P., Khoshgozaran, A., Shahabi, C., Tan, K.-L.: Private queries in location based services: anonymizers are not necessary. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, Vancouver, Canada, June 09-12 (2008)
Shin, H., Vaidya, J., Atluri, V.: A profile anonymization model for privacy in a personalized location based service environment mobile data management. In: 9th International Conference on MDM 2008, April 27-30, pp. 73–80 (2008)
Xu, Y., Wang, K., Yang, G., Fu, A.W.C.: Online anonymity for personalized web services. In: Proceeding of the 18th ACM Conference on Information and Knowledge Management, Hong Kong, China, November 02-06 (2009)
Shen, Y., Liu, Y., Zhang, Y.: Personalized-Granular k-Anonymity. In: International Conference on Information Engineering and Computer Science, ICIECS 2009, December 19-20, pp. 1–4 (2009)
Toubiana, V., Narayanan, A., Boneh, D., Nissenbaum, H., Barocas, S.: Adnostic: Privacy preserving targeted advertising. In: NDSS (2010)
Fredrikson, M., Livshits, B.: RePriv: Re-imagining content personalization and in-browser privacy. In: 2011 IEEE Symposium on Security and Privacy (SP), May 22-25, pp. 131–146 (2011)
Chen, T., Han, W.-L., Wang, H.-D., Zhou, Y.-X., Xu, B., Zang, B.-Y.: Content Recommendation system based on private dynamic user profile. In: 2007 International Conference on Machine Learning and Cybernetics, August 19-22, vol. 4, pp. 2112–2118 (2007)
Shen, X., Tan, B., Zhai, C.: Implicit user modeling for personalized search. In: CIKM 2005: Proceedings of the 14th ACM International Conference on Information and Knowledge Management, pp. 824–831. ACM (2005)
Shankar, U., Karlof, C.: Doppelganger: Better browser privacy without the bother. In: Proceedings of the 13th ACM Conference on Computer and Communications Security (CCS 2006) (2006)
Brar, A., Kay, J.: Privacy and Security in Ubiquitous Personalized Applications. In: Proc. User Modelling Workshop on Privacy-Enhanced Personalization, Edinburgh, UK, July 25 (2005)
Langheinrich, M.: A privacy awareness system for ubiquitous computing environments. In: Borriello, G., Holmquist, L.E. (eds.) UbiComp 2002. LNCS, vol. 2498, p. 237. Springer, Heidelberg (2002)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Kolias, C., Kolias, V., Kambourakis, G., Kayafas, E. (2013). A Client-Side Privacy Framework for Web Personalization. In: Anagnostopoulos, I., Bieliková, M., Mylonas, P., Tsapatsoulis, N. (eds) Semantic Hyper/Multimedia Adaptation. Studies in Computational Intelligence, vol 418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28977-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-28977-4_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28976-7
Online ISBN: 978-3-642-28977-4
eBook Packages: EngineeringEngineering (R0)