Thursday 28th of March 2024
 

Privacy Preserving Association Rule Mining based on the Intersection Lattice and Impact Factor of Items


Bonam Janakiramaiah, Ramamohan Reddy A and Kalyani G

Association Rules revealed by association rule mining may contain some sensitive rules, which may cause prospective threats towards privacy and protection. A number of researchers in this area have recently made efforts to preserve privacy for sensitive association rules in transactional databases. In this paper, we put forward a heuristic based association rule hiding algorithm to get rid of the sensitive knowledge from the released database based on the intersection lattice of an item. The projected algorithm specifies the victim item based on the concept of impact factor of an item in the sensitive rule on the non sensitive frequent item sets. The impact factor of an item in the sensitive association rule is equal to the number of non sensitive frequent item sets that are affected by removing that item from the required number of transactions. Lower the impact factor of an item, lower is its effect on the non sensitive frequent item sets. Proposed algorithm exhibits the concept of intersection lattice and impact factor to conceal several rules by modifying less significant number transactions. As modifications are fewer, data excellence is very less exaggerated.

Keywords: Association Rules, Privacy Preserving, Intersection lattice, Sanitization, Data distortion.

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ABOUT THE AUTHORS

Bonam Janakiramaiah
He was born in 1979. He received his bachelor’s degree in Computer Science and Engineering from Nagpur University, Masters in Computer Science and Engineering from Jawaharlal Nehru Technological University. He is currently working as Associate Professor in DVR & Dr HS MIC College of Technology, Kanchikacherla, India. He is now research scholar in JNTUH, Hyderabad, India. His interests are Privacy preserving data mining, Machine Learning, Soft Computing.

Ramamohan Reddy A
He was born in 1958. He received his Masters in Computer Science and Engineering from NIT, Warangal, Ph.D in Computer Science and Engineering from Sri Venkateswara University, Tirupati. He is currently working as a Professor and Head of Computer Science and Engineering department in SVU College of Engineering, Tirupati, India. His interests are Data Mining, Software Engineering and Software Architectures.

Kalyani G
She was born in 1979. She received her bachelor’s degree in Computer Science and Engineering from Acharya Nagarjuna University, Masters in Computer Science and Engineering from Jawaharlal Nehru Technological University. She is currently working as Associate Professor in DVR & Dr HS MIC College of Technology, Kanchikacherla, India. Her interests are Privacy preserving data mining, Machine Learning, Operating Systems, Data Base Management Systems.


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