Data monitoring confidentiality and the grid
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Data Monitoring Confidentiality and the Grid. Mark Elliot Confidentiality And Privacy Group (www.ccsr.ac.uk/capri) University of Manchester. Overview. Data Data Everywhere…. The Grid and its potential New confidentiality problems and opportunities Data Environment Analysis.

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Data monitoring confidentiality and the grid

Data Monitoring Confidentialityand the Grid

Mark Elliot

Confidentiality And Privacy Group

(www.ccsr.ac.uk/capri)

University of Manchester


Overview

Overview

  • Data Data Everywhere….

  • The Grid and its potential

  • New confidentiality problems and opportunities

  • Data Environment Analysis


Data data everywhere

Data Data Everywhere…

  • Massive and exponential increase in data; Mackey and Purdam(2002); Purdam and Elliot(2002).

    • These studies have led to the setting up of the data monitoring service.

  • Singer(1999) noted three behavioural tendencies:

    • Collect more information on each population unit

    • Replace aggregate data with person specific databases

    • Given the opportunity collect personal information

  • Purdam and Elliot add:

    • Link data whenever you can


The grid

The Grid

  • “Integrated infrastructure for high-performance distributed computation” Cannataro and Talia (2002)

    • Grid middleware handles the technical issues communication, security, access/authentication etc… Cole et al (2002)

  • Data grid

  • Knowledge grid


A blurring of concepts

A Blurring of Concepts

  • The boundaries between data and processes become less distinct

    • Non-static datasets

    • One persons output is another person’s data


Combining and enhancing data

Combining and Enhancing Data

  • Record linkage

  • Data fusion

  • Simulation

  • Verification

    • Of data

    • Of output


Data mining and the grid

Data Mining and the Grid

  • Traditional Data Mining examines and identifies patterns on single (if massive) datasets.

  • But Data Mining is really a method/ approach/ technology that has been waiting for the grid to happen. Multi dataset mining is now becoming a reality.


Agents

Agents

  • AI concept

  • Active programs capable of directed ‘intelligent’ search and manipulation. Web crawlers

  • Building blocks of dynamic grid?


A look over the horizon

A Look Over the Horizon

  • Absolute Seamlesness.

    • The ability to sit at a computer/terminal and request the information one requires.

      • In natural language.

  • Real-time dynamic modelling and simulation.


Data monitoring confidentiality and the grid

But…………

  • Human issues

    • Closer to artificial consciousness

      • Admit machines into our moral universe

    • Technological Interdependence

    • Confidentiality and privacy


Confidentiality issues and opportunities

Confidentiality issues and opportunities

  • Data Linkage increases disclosure risk

    BUT

  • Indirect Data Access allows a new method of controlling disclosure and increase analytical power.


Data monitoring confidentiality and the grid

Tentative Architecture for complete system for disclosure control in remote access systems.

Firewall

Raw Data

PRE-ACCESS DQI Monitor

PRE-ACCESS SDRA/SDC

Treated Data

PRE-Output DQI Monitor

PRE-OUTPUT SDRA/SDC

Data Intrusionsentry

Analytical

Requests

Analytical

Output


Data environment analysis

Data Environment Analysis

  • Need to move with the technology from:

    • One shot analyses of individual datasets

    • Ongoing analyses of the data environment

  • The question is Not how safe is my data but how disclosive is the data environment.

  • A process of data monitoring is one aspect of this.


What sort of society

What sort of society?

  • Informational Transparency?

  • Human- Computer Interdependence?

  • Individualism vs Collectivism

  • A choice:

  • More legislation or less?

  • Personal information a commodity or public good


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