STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data
Machine Learning
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Applying the Subdue Substructure Discovery System to the Chemical Toxicity Domain
Proceedings of the Twelfth International Florida Artificial Intelligence Research Society Conference
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Building decision tree classifier on private data
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Privacy-preserving k-means clustering over vertically partitioned data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy preserving regression modelling via distributed computation
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Optimal randomization for privacy preserving data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy-Preserving Outlier Detection
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Privacy-preserving distributed k-means clustering over arbitrarily partitioned data
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Discovering Frequent Graph Patterns Using Disjoint Paths
IEEE Transactions on Knowledge and Data Engineering
Secure set intersection cardinality with application to association rule mining
Journal of Computer Security
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Privacy-preserving decision trees over vertically partitioned data
ACM Transactions on Knowledge Discovery from Data (TKDD)
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
An improved algorithm for computing logarithms over and its cryptographic significance (Corresp.)
IEEE Transactions on Information Theory
Mining frequent graph patterns with differential privacy
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
| Hi-index | 0.00 |
Graph structured data can be found in many domains and applications. Analysis of such data can give valuable insights. Frequent subgraph discovery, the problem of finding the set of subgraphs that is frequent among the underlying database of graphs, has attracted a lot of recent attention. Many algorithms have been proposed to solve this problem. However, all assume that the entire set of graphs is centralized at a single site, which is not true in a lot of cases. Furthermore, in a lot of interesting applications, the data is sensitive (for example, drug discovery, clique detection, etc). In this paper, we address the problem of privacy-preserving subgraph discovery. We propose a flexible approach that can utilize any underlying frequent subgraph discovery algorithm and uses cryptographic primitives to preserve privacy. The comprehensive experimental evaluation validates the feasibility of our approach.