Data Preparation for User Profiling from Traffic Log

KUMPOŠT, Marek. Data Preparation for User Profiling from Traffic Log. In Proceedings of The International Conference on Emerging Security Information, Systems, and Technologies (SECURWARE 2007). Los Alamitos, CA, USA: IEEE Computer Society, 2007, p. 89-94. ISBN 0-7695-2989-5.

Basic information

Original name

Data Preparation for User Profiling from Traffic Log

Name in Czech

Příprava dat pro profilování

Authors

KUMPOŠT, Marek (203 Czech Republic, guarantor)

Edition

Los Alamitos, CA, USA, Proceedings of The International Conference on Emerging Security Information, Systems, and Technologies (SECURWARE 2007), p. 89-94, 6 pp. 2007

Publisher

IEEE Computer Society

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

RIV identification code

RIV/00216224:14330/07:00032428

Organization unit

Faculty of Informatics

ISBN

0-7695-2989-5

Keywords in English

user profiling; data mining; traffic log; privacy protection; user profiles

Tags

data mining, privacy protection, traffic log, user profiles, user profiling

Tags

International impact, Reviewed

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Abstract

V originále

User profiling is a technique that services use to provide customizable content to their users. These services operate with a user profile that reflects users' behaviour in the past. Profiling gives us some evidence about users' behaviour (information about their interests and social background). Instead of requiring users to state their interests, a service could learn this information from users' past activities. The main question is how much private information can be derived from context information that is related to an individual. The second question is to what extent a behaviour pattern can be used to pinpoint an individual among others.

In Czech

User profiling is a technique that services use to provide customizable content to their users. These services operate with a user profile that reflects users' behaviour in the past. Profiling gives us some evidence about users' behaviour (information about their interests and social background). Instead of requiring users to state their interests, a service could learn this information from users' past activities. The main question is how much private information can be derived from context information that is related to an individual. The second question is to what extent a behaviour pattern can be used to pinpoint an individual among others.