<P> k - anonymity is a property possessed by certain anonymized data . The concept of k - anonymity was first introduced by Latanya Sweeney and Pierangela Samarati in a paper published in 1998 as an attempt to solve the problem: "Given person - specific field - structured data, produce a release of the data with scientific guarantees that the individuals who are the subjects of the data cannot be re-identified while the data remain practically useful ." A release of data is said to have the k - anonymity property if the information for each person contained in the release cannot be distinguished from at least k - 1 individuals whose information also appear in the release . The various procedures and programs for generating anonymised data providing k - anonymity protection have been patented in the United States (Patent 7,269,578). </P> <P> In the context of k - anonymization problems, a database is a table with n rows and m columns . Each row of the table represents a record relating to a specific member of a population and the entries in the various rows need not be unique . The values in the various columns are the values of attributes associated with the members of the population . The following table is a nonanonymized database consisting of the patient records of some fictitious hospital in Kochi . </P> <Table> <Tr> <Th> Name </Th> <Th> Age </Th> <Th> Gender </Th> <Th> State of domicile </Th> <Th> Religion </Th> <Th> Disease </Th> </Tr> <Tr> <Td> Ramsha </Td> <Td> 29 </Td> <Td> Female </Td> <Td> Tamil Nadu </Td> <Td> Hindu </Td> <Td> Cancer </Td> </Tr> <Tr> <Td> Yadu </Td> <Td> 24 </Td> <Td> Female </Td> <Td> Kerala </Td> <Td> Hindu </Td> <Td> Viral infection </Td> </Tr> <Tr> <Td> Salima </Td> <Td> 28 </Td> <Td> Female </Td> <Td> Tamil Nadu </Td> <Td> Muslim </Td> <Td> TB </Td> </Tr> <Tr> <Td> Sunny </Td> <Td> 27 </Td> <Td> Male </Td> <Td> Karnataka </Td> <Td> Parsi </Td> <Td> No illness </Td> </Tr> <Tr> <Td> Joan </Td> <Td> 24 </Td> <Td> Female </Td> <Td> Kerala </Td> <Td> Christian </Td> <Td> Heart - related </Td> </Tr> <Tr> <Td> Bahuksana </Td> <Td> 23 </Td> <Td> Male </Td> <Td> Karnataka </Td> <Td> Buddhist </Td> <Td> TB </Td> </Tr> <Tr> <Td> Rambha </Td> <Td> 19 </Td> <Td> Male </Td> <Td> Kerala </Td> <Td> Hindu </Td> <Td> Cancer </Td> </Tr> <Tr> <Td> Kishor </Td> <Td> 29 </Td> <Td> Male </Td> <Td> Karnataka </Td> <Td> Hindu </Td> <Td> Heart - related </Td> </Tr> <Tr> <Td> Johnson </Td> <Td> 17 </Td> <Td> Male </Td> <Td> Kerala </Td> <Td> Christian </Td> <Td> Heart - related </Td> </Tr> <Tr> <Td> </Td> <Td> 19 </Td> <Td> Male </Td> <Td> Kerala </Td> <Td> Christian </Td> <Td> Viral infection </Td> </Tr> </Table>

A measure using algorithms to publically protect patient identifiable information is