학술논문

Author Privacy, Data Fabrication, and Knowledge Discovery in Databases
Document Type
Conference
Source
2006 Innovations in Information Technology Innovations in Information Technology, 2006. :1-5 Nov, 2006
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Data privacy
Fabrication
Databases
Machine learning
Internet
Data mining
Computer science
Data analysis
Delta modulation
Learning systems
Language
Abstract
The problem of data fabrication, due to heightened consumer concerns about privacy, is on the rise. The unique characteristic of the Internet, anonymity, is a probable contributor to the intention of users to fabricate information. We propose a technological solution to this problem based on the deployment of Knowledge Discovery in Database (KDD) systems to learn discrimination functions that discriminate between correct and fabricated data. These discrimination functions can then be used to form filters that remove falsified data from marketing data. That such discrimination functions are possible is due to the characteristic form falsified data takes. The greatest hurdle to implementing this approach is the availability of data labeled as "falsified" and "correct." However, the proposed technological solution offers potential to marketers and businesses alike