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Data Monitoring Confidentiality and the Grid Mark Elliot Confidentiality And Privacy Group (www.ccsr.ac.uk/capri) University of Manchester
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Overview Data Data Everywhere…. The Grid and its potential New confidentiality problems and opportunities Data Environment Analysis
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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
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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
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A Blurring of Concepts The boundaries between data and processes become less distinct –Non-static datasets –One persons output is another persons data
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Combining and Enhancing Data Record linkage Data fusion Simulation Verification –Of data –Of output
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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.
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Agents AI concept Active programs capable of directed intelligent search and manipulation. Web crawlers Building blocks of dynamic grid?
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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.
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But………… Human issues Closer to artificial consciousness –Admit machines into our moral universe Technological Interdependence Confidentiality and privacy
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Confidentiality issues and opportunities Data Linkage increases disclosure risk BUT Indirect Data Access allows a new method of controlling disclosure and increase analytical power.
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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.
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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.
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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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