Hiding sensitive predictive frequent itemsets

Yildiz B., Ergenç B.

International MultiConference of Engineers and Computer Scientists 2011, IMECS 2011, Kowloon, Hong Kong, 16 - 18 Mart 2011, cilt.1, ss.339-345, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 1
  • Basıldığı Şehir: Kowloon
  • Basıldığı Ülke: Hong Kong
  • Sayfa Sayıları: ss.339-345
  • Anahtar Kelimeler: Frequent itemset mining, Privacy preserving data mining, Sensitive itemset hiding
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

In this work, we propose an itemset hiding algorithm with four versions that use different heuristics in selecting the item in itemset and the transaction for distortion. The main strengths of itemset hiding algorithm can be stated as i) it works without pre-mining so privacy breech caused by revealing frequent itemsets in advance is prevented and efficiency is increased, ii) base algorithm (Matrix-Apriori) works without candidate generation so efficiency is increased, iii) sanitized database and frequent itemsets of this database are given as outputs so no post-mining is required and iv) simple heuristics like the length of the pattern and the frequency of the item in the pattern are used for selecting the item for distortion. We compare versions of our itemset hiding algorithm by their side effects, runtimes and distortion on original database.