Issues in Privacy Preservation for Re-Publishable Data
Pachara Tinamas, Juggapong Natwichai · Advances in parallel computing · 2020
In order to preserve the privacy in the scenarios where the data can be changed by the insert, update, and delete operations, at all times or re-publishable situation, the non-static existing approaches and algorithms may not be appropriate. The changing of data in a volatile environment, e.g. edge computing model with distributed datasources, could even escalate the issue in term of effectiveness and efficiency. In this paper, we elaborate the issues to address such problem. First, the background of privacy preservation is presented. Subsequently, we show the environment of the re-publishable dataset problem. Then, the analysis of possible privacy breach is illustrated. Finally, the paper is summarized and the problem is formally presented and discussed.