De-Identification of Personally Identifiable Information

IAPP Practical Privacy Series 2012, New York
This is the age of big data, where massive amounts of information or data from multiple sources are being collected, linked together and analyzed by organizations in different industries for many different purposes. This data tends to be personal in that it characterizes individual human behaviors such as their Internet surfing patters, purchasing behavior in stores, individual health information, details on financial transactions and physical movements to name just a few examples. All of this personal information, especially when combined, paints a detailed picture about individuals, their likes and dislikes, what they do and when and where they do it. This raises important and highly sensitive privacy issues. There is much debate and deliberation on this topic. Join us to examine the need to de-identify personally identifiable information/data in a defensible way and the methodologies used to de-identify data so that it can be leveraged for new purposes. Plus, we’ll use case studies to illustrate how these de-identified and disclosed data sets can still retain significant utility. Speaker: Khaled El Emam, Founder and CEO, Privacy Analytics, Inc.
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