Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Information filtering based on user behavior analysis and best match text retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Information Filtering: A New Two-Phase Model Using StereotypicUser Profiling
Journal of Intelligent Information Systems - Special issue: next generation information technologies and systems
Crowds: anonymity for Web transactions
ACM Transactions on Information and System Security (TISSEC)
Communications of the ACM
TRUSTe: an online privacy seal program
Communications of the ACM
Anonymous Web transactions with Crowds
Communications of the ACM
Decision Support Systems - From information retrieval to knowledge management: enabling technologies and best practices
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
The State of the Art in Text Filtering
User Modeling and User-Adapted Interaction
Information Filtering: Overview of Issues, Research and Systems
User Modeling and User-Adapted Interaction
How to Make Personalized Web Browising Simple, Secure, and Anonymous
FC '97 Proceedings of the First International Conference on Financial Cryptography
Proceedings of the First International Workshop on Information Hiding
Anonymous Connections and Onion Routing
SP '97 Proceedings of the 1997 IEEE Symposium on Security and Privacy
Association rules mining in vertically partitioned databases
Data & Knowledge Engineering - Special issue: WIDM 2004
Privacy preservation improvement by learning optimal profile generation rate
UM'03 Proceedings of the 9th international conference on User modeling
Exploiting social networks to provide privacy in personalized web search
Journal of Systems and Software
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Privacy is becoming a serious challenge in computerized environments, especially the Web where many companies constantly attempt to violate the privacy of users. When a user requests a service on the Internet, an eavesdropper can reveal his identity, the WEB site he accesses (end server), the link between them, and infer private information about the user. The computer security community has concentrated on improving user privacy by hiding his identifiable tracks on the WEB, thus assuring his anonymity while surfing. However, users may want or need to identify themselves over the net but still retain their information needs and profile in private. The privacy model suggested in this paper is aimed at preserving users' privacy while allowing them to identify themselves to various services, and prevents eavesdroppers from using identifiable users' tracks to construct a user profile. The model is based on the generation of faked transactions in various fields of interest in order to prevent the eavesdropper from accurate derivation of the user profile. The basic idea underlying the model is to confuse the eavesdropper's automated programs with wrong data. A privacy measure is defined that reflects the degree of confusion a system can cause to the eavesdropper. A prototype system was developed to check the feasibility of the model and to conduct experiments to examine its effectiveness.