Title :
A Proposal Towards Customers´ Privacy Preference Policy
Author :
Wei, Ran ; Zhan, Justin
Author_Institution :
Carnegie Mellon CyLab Japan, Kobe
Abstract :
Increasingly, companies hold more and more data about their customers. This data is seen as useful for the company, although often customers do not wish to share their personal data. Methods such as P3P for verifying a company´s privacy policy are available, however, they do not provide much choice to the customer, and they provide an all-or-nothing approach. We explore the privacy preference policy approach which attempts to align the privacy preferences of the individual with that of a company. We further critique this method and develop it to incorporate levels of importance and priority.
Keywords :
data privacy; security of data; customer privacy preference policy; personal data; Books; Companies; Cybernetics; Data privacy; Internet; Law; Machine learning; Proposals; Protection; Radio access networks; Critical information; Privacy preference policy (PPP); Sensitive information;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370666