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2011

Integrated exact, hybrid and metaheuristic learning methods for confidentiality protection

9 years 3 months ago
Integrated exact, hybrid and metaheuristic learning methods for confidentiality protection
A vital task facing government agencies and commercial organizations that report data is to represent the data in a meaningful way and simultaneously to protect the confidentiality of critical components of this data. The challenge is to organize and disseminate data in a form that prevents such critical components from being inferred by groups bent on corporate espionage, to gain competitive advantages, or having a desire to penetrate the security of the information underlying the data. Controlled tabular adjustment is a recently developed approach for protecting sensitive information by imposing a special form of statistical disclosure limitation on tabular data. The underlying model gives rise to a mixed integer linear programming problem involving both continuous and discrete (zero-one) variables. We develop stratified ordered (s-ordered) heuristics and a new meta-heuristic learning approach for solving this model, and compare their performance to previous heuristics and to an exa...
Fred Glover, Lawrence H. Cox, Rahul Patil, James P
Added 12 May 2011
Updated 12 May 2011
Type Journal
Year 2011
Where ANOR
Authors Fred Glover, Lawrence H. Cox, Rahul Patil, James P. Kelly
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