Breaking the Arc: Risk control for Big Data

The use of Big Data technologies and analytics have the potential to revolutionise the world. The mass instrumentation of the planet and society is providing intelligence that is not only enhancing our personal lives, but also opening up new opportunities for addressing some of key environmental, so...

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Main Authors: Hodges, D, Creese, S
Format: Conference item
Published: 2013
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author Hodges, D
Creese, S
author_facet Hodges, D
Creese, S
author_sort Hodges, D
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description The use of Big Data technologies and analytics have the potential to revolutionise the world. The mass instrumentation of the planet and society is providing intelligence that is not only enhancing our personal lives, but also opening up new opportunities for addressing some of key environmental, social and economic challenges of the 21st century. Unfortunately, as with all technology, there is the potential for misuse; in the case of personal data the ability to gather, enrich and mine at extreme pace and volume could result in societal-scale privacy intrusions. We apply a model for identity across cyber and physical spaces to the question of risk control for personal-data in the context of big data analytics. Using a graphical model for identity we reflect on the response options we have and how such risk controls may or may not be effective.
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spelling oxford-uuid:6e28a6d4-c4be-4dc6-925b-bd22f8df89ef2022-03-26T19:22:28ZBreaking the Arc: Risk control for Big DataConference itemhttp://purl.org/coar/resource_type/c_5794uuid:6e28a6d4-c4be-4dc6-925b-bd22f8df89efDepartment of Computer Science2013Hodges, DCreese, SThe use of Big Data technologies and analytics have the potential to revolutionise the world. The mass instrumentation of the planet and society is providing intelligence that is not only enhancing our personal lives, but also opening up new opportunities for addressing some of key environmental, social and economic challenges of the 21st century. Unfortunately, as with all technology, there is the potential for misuse; in the case of personal data the ability to gather, enrich and mine at extreme pace and volume could result in societal-scale privacy intrusions. We apply a model for identity across cyber and physical spaces to the question of risk control for personal-data in the context of big data analytics. Using a graphical model for identity we reflect on the response options we have and how such risk controls may or may not be effective.
spellingShingle Hodges, D
Creese, S
Breaking the Arc: Risk control for Big Data
title Breaking the Arc: Risk control for Big Data
title_full Breaking the Arc: Risk control for Big Data
title_fullStr Breaking the Arc: Risk control for Big Data
title_full_unstemmed Breaking the Arc: Risk control for Big Data
title_short Breaking the Arc: Risk control for Big Data
title_sort breaking the arc risk control for big data
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