STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Secure multi-party computation problems and their applications: a review and open problems
Proceedings of the 2001 workshop on New security paradigms
Secure Multi-party Computational Geometry
WADS '01 Proceedings of the 7th International Workshop on Algorithms and Data Structures
Privacy preserving association rule mining in vertically partitioned data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
A practical approach to solve Secure Multi-party Computation problems
Proceedings of the 2002 workshop on New security paradigms
Privacy-Preserving Cooperative Statistical Analysis
ACSAC '01 Proceedings of the 17th Annual Computer Security Applications Conference
Foundations of Cryptography: Volume 2, Basic Applications
Foundations of Cryptography: Volume 2, Basic Applications
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Fairplay—a secure two-party computation system
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Secrecy of two-party secure computation
DBSec'05 Proceedings of the 19th annual IFIP WG 11.3 working conference on Data and Applications Security
Toward empirical aspects of secure scalar product
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews - Special issue on information reuse and integration
| Hi-index | 0.00 |
Privacy protection has become one of the most important issues in the information era. Consequently, many protocols have been developed to achieve the goal of accomplishing a computational task cooperatively without revealing the participants' private data. Practical protocols, however, do not guarantee perfect privacy protection, as some degree of privacy leakage is allowed so that resources can be used efficiently, e.g., the number of random bits required and the computation time. A metric for measuring the degree of information leakage based on an information theoretical framework was proposed in [2]. Based on that formal framework, we present a lower bound of the scalar product problem in this paper, and show that to solve the problem without the help of a third party, approximately half the private information must be revealed. To better capture our intuition about the secrecy of various protocols, we propose two more measurements: evenness and spread. The first measures how evenly the information leakage is distributed among the participants' private inputs. The second measures the size of the smallest set an adversary could use to obtain the same ratio of leaked information that could be derived in the worst case scenario.