Presentation on theme: "Data Monitoring Confidentiality and the Grid Mark Elliot Confidentiality And Privacy Group (www.ccsr.ac.uk/capri) University of Manchester."— Presentation transcript:
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
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 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 The boundaries between data and processes become less distinct –Non-static datasets –One persons output is another persons data
Combining and Enhancing Data Record linkage Data fusion Simulation Verification –Of data –Of output
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 AI concept Active programs capable of directed intelligent search and manipulation. Web crawlers Building blocks of dynamic grid?
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.
But………… Human issues Closer to artificial consciousness –Admit machines into our moral universe Technological Interdependence Confidentiality and privacy
Confidentiality issues and opportunities Data Linkage increases disclosure risk BUT Indirect Data Access allows a new method of controlling disclosure and increase analytical power.
PRE-ACCESS DQI Monitor Raw Data Treated Data Data Intrusion sentry Analytical Requests PRE-OUTPUT SDRA/SDC PRE-ACCESS SDRA/SDC PRE-Output DQI Monitor Analytical Output Firewall Tentative Architecture for complete system for disclosure control in remote access systems.
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? Informational Transparency? Human- Computer Interdependence? Individualism vs Collectivism A choice: More legislation or less? Personal information a commodity or public good