Computer Engineering Commons^™

Interval Approach To Preserving Privacy In Statistical Databases: Related Challenges And Algorithms Of Computational Statistics, Luc Longpre, Gang Xiang, Vladik Kreinovich, Eric Freudenthal

Departmental Technical Reports (CS)

In many practical situations, it is important to store large amounts of data and to be able to statistically process the data. A large part of the data is confidential, so while we welcome statistical data processing, we do not want to reveal sensitive individual data. If we allow researchers to ask all kinds of statistical queries, this can lead to violation of people's privacy. A sure-proof way to avoid these privacy violations is to store ranges of values (e.g., between 40 and 50 for age) instead of the actual values. This idea solves the privacy problem, but it leads …