TY - GEN
T1 - Privacy-preserving subgraph discovery
AU - Mehmood, Danish
AU - Shafiq, Basit
AU - Vaidya, Jaideep
AU - Hong, Yuan
AU - Adam, Nabil
AU - Atluri, Vijayalakshmi
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84864372044&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864372044&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-31540-4_13
DO - 10.1007/978-3-642-31540-4_13
M3 - Conference contribution
AN - SCOPUS:84864372044
SN - 9783642315398
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 161
EP - 176
BT - Data and Applications Security and Privacy XXVI - 26th Annual IFIP WG 11.3 Conference, DBSec 2012, Proceedings
T2 - 26th Annual WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2012
Y2 - 11 July 2012 through 13 July 2012
ER -