Update README.md

README.md

@@ -42,7 +42,7 @@ The paradigm of k-anonymity offers "safety in numbers" – combinations of a
 
 "All attribute combinations in this synthetic dataset describe groups of 10 or more individuals in the original sensitive dataset, therefore may never be used to infer the presence of individuals or groups smaller than 10."
 
-Our approach to synthesizing data with k-anonymity overcomes many of the limitations of standard [k-anonymization](https://en.wikipedia.org/wiki/K-anonymity), in which attributes of sensitive data records are generalized and suppressed until k-anonymity is reached, and only for those attributes determined in advance to be potentially identifying when used in combination (so-called quasi-identifiers). In this standard approach, other attributes all remaining sensitive attributes as released so long as k-anonymity holds for the designated quasi-identifiers. This makes the records (and thus subjects) of k-anonymized datasets susceptible to linking attacks based on auxilliary data or background knowledge.
+Our approach to synthesizing data with k-anonymity overcomes many of the limitations of standard [k-anonymization](https://en.wikipedia.org/wiki/K-anonymity), in which attributes of sensitive data records are generalized and suppressed until k-anonymity is reached, and only for those attributes determined in advance to be potentially identifying when used in combination (so-called quasi-identifiers). In this standard approach, all remaining sensitive attributes are released so long as k-anonymity holds for the designated quasi-identifiers. This makes the records (and thus subjects) of k-anonymized datasets susceptible to linking attacks based on auxilliary data or background knowledge.
 
 In contrast, our k-anonymity synthesizers generate synthetic records that do not represent actual individuals, yet are composed exclusively from common combinations of attributes in the senstive dataset. The k-anonymity guarantee therefore holds for all data columns and all combinations of attributes.