Abstract
In privacy preserving data mining, utility mining plays an important role.
In privacy preserving utility mining, some sensitive itemsets are concealed from the data-
base according to certain privacy policies. Hiding sensitive itemsets from the adversaries
is becoming an important issue nowadays. Also, only very few methods are available in
the literature to hide the sensitive itemsets in the database. One of the existing privacy
preserving utility mining methods utilizes two algorithms, HHUIF and MSICF to con-
ceal the sensitive itemsets, so that the adversaries cannot mine them from the modi ed
database. To accomplish the hiding process, this method nds the sensitive itemsets and
modi es the frequency of the high valued utility items. However, the performance of this
method lacks if the utility value of the items are the same. The items with the same utility
value decrease the hiding performance of the sensitive itemsets and also it has introduced
computational complexity due to the frequency modi cation in each item. To solve this
problem, in this paper a modified HHUIF algorithm with Item Selector (MHIS) is pro-
posed. The proposed MHIS algorithm is a modified version of existing HHUIF algorithm.
The MHIS algorithm computes the sensitive itemsets by utilizing the user defined utility
threshold value. In order to hide the sensitive itemsets, the frequency value of the items
is changed. If the utility values of the items are the same, the MHIS algorithm selects
the accurate items and then the frequency values of the selected items are modified. The
proposed MHIS reduces the computation complexity as well as improves the hiding per-
formance of the itemsets. The algorithm is implemented and the resultant itemsets are
compared against the itemsets that are obtained from the conventional privacy preserving
utility mining algorithms.