The future of statistical disclosure control

12/21/2018
by   Mark Elliot, et al.
0

Statistical disclosure control (SDC) was not created in a single seminal paper nor following the invention of a new mathematical technique, rather it developed slowly in response to the practical challenges faced by data practitioners based at national statistical institutes (NSIs). SDC's subsequent emergence as a specialised academic field was an outcome of three interrelated socio-technical changes: (i) the advent of accessible computing as a research tool in the 1980s meant that it became possible - and then increasingly easy - for researchers to process larger quantities of data automatically; this naturally increased demand for such data; (ii) it became possible for data holders to process and disseminate detailed data as digital files and (iii) the number of organisations holding data about individuals proliferated. This also meant the number of potential adversaries with the resources to attack any given dataset increased exponentially. In this article, we describe the state of the art for SDC and then discuss the core issues and future challenges. In particular, we touch on SDC and big data, on SDC and machine learning, and on SDC and anti-discrimination.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 14

page 18

page 20

page 23

page 24

page 25

page 27

01/09/2021

Scientific Relevance and Future of Digital Immortality and Virtual Humans

We are on the threshold of a significant change in the way we view digit...
08/07/2013

Challenges of Big Data Analysis

Big Data bring new opportunities to modern society and challenges to dat...
09/09/2015

Statistical Inference, Learning and Models in Big Data

The need for new methods to deal with big data is a common theme in most...
10/06/2021

Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development

Practitioners from diverse occupations and backgrounds are increasingly ...
10/16/2018

Improving Data Quality through Deep Learning and Statistical Models

Traditional data quality control methods are based on users experience o...
12/28/2017

Field Studies with Multimedia Big Data: Opportunities and Challenges (Extended Version)

Social multimedia users are increasingly sharing all kinds of data about...
05/27/2020

Breiman's "Two Cultures" Revisited and Reconciled

In a landmark paper published in 2001, Leo Breiman described the tense s...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.