Data Valuation to Minimize Monetary Loss

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Publish Date: 
Thursday, September 22, 2016
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Abstract: 

Data protection algorithms that replicate data based on its value can minimize monetary loss in the case of a disaster (reference Omer/Peleg/Udi work). The value of data, however, is often input manually and enumerated into broad categories (e.g. low, medium, high). The industry would benefit from approaches that automatically calculate specific numeric scores and dynamically adjusts protection algorithms based on these more fine-grained results. This presentation (a) introduces a research program on data value, (b) proposes techniques for calculating data value and (c) discusses a framework for feeding valuation results into a data protection ecosystem.