HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Privacy-Preserving Data Mining: A Game-Theoretic Approach

Abstract : Privacy-preserving data mining has been an active research area in recent years due to privacy concerns in many distributed data mining settings. Protocols for privacy-preserving data mining have considered semi-honest, malicious, and covert adversarial models in cryptographic settings, whereby an adversary is assumed to follow, arbitrarily deviate from the protocol, or behaving somewhere in between these two, respectively. Semi-honest model provides weak security requiring small amount of computation, on the other hand, malicious and covert models provide strong security requiring expensive computations like homomorphic encryptions. However, game theory allows us to design protocols where parties are neither honest nor malicious but are instead viewed as rational and are assumed (only) to act in their own self-interest. In this paper, we build efficient and secure set-intersection protocol in game-theoretic setting using cryptographic primitives. Our construction avoids the use of expensive tools like homomorphic encryption and oblivious transfer. We also show that our protocol satisfies computational versions of strict Nash equilibrium and stability with respect to trembles.
Document type :
Conference papers
Complete list of metadata

Cited literature [36 references]  Display  Hide  Download

Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Wednesday, September 13, 2017 - 8:55:54 AM
Last modification on : Wednesday, September 13, 2017 - 2:28:20 PM
Long-term archiving on: : Thursday, December 14, 2017 - 12:38:10 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



Atsuko Miyaji, Mohammad Rahman. Privacy-Preserving Data Mining: A Game-Theoretic Approach. 23th Data and Applications Security (DBSec), Jul 2011, Richmond, VA, United States. pp.186-200, ⟨10.1007/978-3-642-22348-8_15⟩. ⟨hal-01586580⟩



Record views


Files downloads