In attribute suppression, sensitive attributes are removed as a single cell, tuple or entire column from the dataset. Instead of the entire column (variable), only specific records are removed from the dataset in record suppression.
Published in Chapter:
Personal Data Privacy and Protection in the Meeting, Incentive, Convention, and Exhibition (MICE) Industry
M. Fevzi Esen (Istanbul Medeniyet University, Turkey) and Eda Kocabas (Istanbul Medeniyet University, Turkey)
Copyright: © 2019
|Pages: 27
DOI: 10.4018/978-1-5225-7432-3.ch023
Abstract
With the new developments in information technologies, personal and business data have become easily accessible through different channels. The huge amounts of personal data across global networks and databases have provided crucial benefits in a scientific manner and many business opportunities, also in the meeting, incentive, convention, and exhibition (MICE) industry. In this chapter, the authors focus on the analysis of MICE industry with regards to the new regulation (GDPR) of personal data protection of all EU citizens and how the industry professionals can adapt their way of business in light of this new regulation. The authors conducted an online interview with five different meetings industry professionals to have more insight about the data produced with its content and new regulations applied to the industry. The importance of personal data privacy and protection is discussed, and the most suitable anonymization techniques for personal data privacy are proposed.