Fully homomorphic encryption based two-party association rule mining

2012 ◽  
Vol 76-78 ◽  
pp. 1-15 ◽  
Author(s):  
Mohammed Golam Kaosar ◽  
Russell Paulet ◽  
Xun Yi
Keyword(s):  
Association Rule ◽  
Association Rule Mining ◽  
Homomorphic Encryption ◽  
Rule Mining ◽  
Fully Homomorphic Encryption

Secure Two-Party Association Rule Mining Based on One-Pass FP-Tree

2013 ◽  
pp. 82-102
Author(s):  
Golam Kaosar ◽  
Xun Yi
Keyword(s):  
Association Rules ◽  
Association Rule ◽  
Association Rule Mining ◽  
Data Privacy ◽  
Homomorphic Encryption ◽  
Secure Computation ◽  
Rule Mining ◽  
Fully Homomorphic Encryption ◽  
Popular Method ◽  
Tree Method

Frequent Path tree (FP-tree) is a popular method to compute association rules and is faster than Apriori-based solutions in some cases. Association rule mining using FP-tree method cannot ensure entire privacy since frequency of the itemsets are required to share among participants at the first stage. Moreover, FP-tree method requires two scans of database transactions which may not be the best solution if the database is very large or the database server does not allow multiple scans. In addition, one-pass FP-tree can accommodate continuous or periodically changing databases without restarting the process as opposed to a regular FP-tree based solution. In this paper, the authors propose a one-pass FP-tree method to perform association rule mining without compromising any data privacy among two parties. A fully homomorphic encryption system over integer numbers is applied to ensure secure computation among two data sites without disclosing any number belongs to themselves.

Secure Two-Party Association Rule Mining Based on One-Pass FP-Tree

2011 ◽  
Vol 5 (2) ◽  
pp. 13-32 ◽  
Author(s):  
Golam Kaosar ◽  
Xun Yi
Keyword(s):  
Association Rule ◽  
Association Rule Mining ◽  
Data Privacy ◽  
Homomorphic Encryption ◽  
Secure Computation ◽  
Rule Mining ◽  
Fully Homomorphic Encryption ◽  
Popular Method ◽  
Database Server ◽  
Tree Method

Frequent Path tree (FP-tree) is a popular method to compute association rules and is faster than Apriori-based solutions in some cases. Association rule mining using FP-tree method cannot ensure entire privacy since frequency of the itemsets are required to share among participants at the first stage. Moreover, FP-tree method requires two scans of database transactions which may not be the best solution if the database is very large or the database server does not allow multiple scans. In addition, one-pass FP-tree can accommodate continuous or periodically changing databases without restarting the process as opposed to a regular FP-tree based solution. In this paper, the authors propose a one-pass FP-tree method to perform association rule mining without compromising any data privacy among two parties. A fully homomorphic encryption system over integer numbers is applied to ensure secure computation among two data sites without disclosing any number belongs to themselves.

Analysis and Evaluation of Novel Privacy Preserving Techniques for Collaborative Temporal Association Rule Mining Using Secret Sharing

2014 ◽  
Vol 5 (3) ◽  
pp. 58-76 ◽  
Author(s):  
Nirali R. Nanavati ◽  
Neeraj Sen ◽  
Devesh C. Jinwala
Keyword(s):  
Secret Sharing ◽  
Association Rule ◽  
Association Rule Mining ◽  
Homomorphic Encryption ◽  
Privacy Preserving ◽  
Experimental Results ◽  
Public Key ◽  
Secret Sharing Scheme ◽  
Rule Mining ◽  
Sharing Scheme

With digital data being abundant in today's world, competing organizations desire to gain insights about the market, without putting the privacy of their confidential data at risk. This paper provides a new dimension to the problem of Privacy Preserving Distributed Association Rule Mining (PPDARM) by extending it to a distributed temporal setup. It proposes extensions of public key based and non-public key based additively homomorphic techniques, based on efficient private matching and Shamir's secret sharing, to privately decipher these global cycles in cyclic association rules. Along with the theoretical analysis, it presents experimental results to substantiate it. This paper observes that the Secret Sharing scheme is more efficient than the one based on Paillier homomorphic encryption. However, it observes a considerable increase in the overhead associated with the Shamir's secret sharing scheme, as a result of the increase in the number of parties. To reduce this overhead, it extends the secret sharing scheme without mediators to a novel model with a Fully Trusted and a Semi Trusted Third Party. The experimental results establish this functioning for global cycle detections in a temporal setup as a case study. The novel constructions proposed can also be applied to other scenarios that want to undertake Secure Multiparty Computation (SMC) for PPDARM.

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