UMFE: a user modelling front-end subsystem
International Journal of Man-Machine Studies
Security in computing
Role-Based Access Control Models
Computer
Secure computing: threats and safeguards
Secure computing: threats and safeguards
Introducing SSL and certificates using SSLeay
World Wide Web Journal - Special issue: Web security: a matter of trust
The design, implementation and operation of an email pseudonym server
CCS '98 Proceedings of the 5th ACM conference on Computer and communications security
Speech acts, electronic commerce, and KQML
Decision Support Systems - Special issue: logic modeling
Crowds: anonymity for Web transactions
ACM Transactions on Information and System Security (TISSEC)
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Consistent, yet anonymous, Web access with LPWA
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The platform for privacy preferences
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Anonymous Web transactions with Crowds
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A role-based access control model and reference implementation within a corporate intranet
ACM Transactions on Information and System Security (TISSEC) - Special issue on role-based access control
Anonymous mechanisms in group decision support systems communication
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One for all and all in one: a learner modelling server in a multi-agent platform
UM '99 Proceedings of the seventh international conference on User modeling
Project “anonymity and unobservability in the Internet”
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Untraceable electronic mail, return addresses, and digital pseudonyms
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A lattice model of secure information flow
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Anonymity, unobservability, and pseudeonymity — a proposal for terminology
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E-privacy in 2nd generation E-commerce: privacy preferences versus actual behavior
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Computer Networks: The International Journal of Computer and Telecommunications Networking
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Cryptography and data security
Cryptography and data security
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Logic-Based Representation and Reasoning for User Modeling Shell Systems
User Modeling and User-Adapted Interaction
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A Review and Analysis of Commercial User Modeling Servers for Personalization on the World Wide Web
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User Modeling for Personalized City Tours
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JATLite: A Java Agent Infrastructure with Message Routing
IEEE Internet Computing
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Agent-Based Engineering, the Web, and Intelligence
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Inference Control in Statistical Databases, From Theory to Practice
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CRYPTO '98 Proceedings of the 18th Annual International Cryptology Conference on Advances in Cryptology
How to Make Personalized Web Browising Simple, Secure, and Anonymous
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Security and Privacy in User Modeling
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Usability meets security - the Identity-Manager as your personal security assistant for the Internet
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The Knowledge Engineering Review
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User-adaptive applications cater to the needs of each individual computer user, taking for example users' interests, level of expertise, preferences, perceptual and motoric abilities, and the usage environment into account. Central user modeling servers collect and process the information about users that different user-adaptive systems require to personalize their user interaction.Adaptive systems are generally better able to cater to users the more data their user modeling systems collect and process about them. They therefore gather as much data as possible and "lay them in stock" for possible future usage. Moreover, data collection usually takes place without users' initiative and sometimes even without their awareness, in order not to cause distraction. Both is in conflict with users' privacy concerns that became manifest in numerous recent consumer polls, and with data protection laws and guidelines that call for parsimony, purpose-orientation, and user notification or user consent when personal data are collected and processed.This article discusses security requirements to guarantee privacy in user-adaptive systems and explores ways to keep users anonymous while fully preserving personalized interaction with them. User anonymization in personalized systems goes beyond current models in that not only users must remain anonymous, but also the user modeling system that maintains their personal data. Moreover, users' trust in anonymity can be expected to lead to more extensive and frank interaction, hence to more and better data about the user, and thus to better personalization. A reference model for pseudonymous and secure user modeling is presented that meets many of the proposed requirements.