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A Comprehensive Comparison of Multiparty Secure Additions with Differential Privacy
1Department of Mathematics & Computer Science, Emory University, Atlanta, GA, USA.
IEEE Transactions on Dependable and Secure Computing
|September 19, 2017
Summary
This study introduces efficient and fault-tolerant secure data aggregation protocols with differential privacy. The enhanced encryption scheme (EFT) and Laplace distributed privacy mechanism (DLPA) offer the best performance and scalability.
Area of Science:
- Computer Science
- Information Security
- Cryptography
Background:
- Secure data aggregation is crucial in distributed systems.
- Ensuring differential privacy for aggregated results is a significant challenge.
- Existing security schemes like Shamir's secret sharing and encryption have limitations.
Purpose of the Study:
- To investigate secure multiparty addition protocols with differential privacy.
- To propose and evaluate a new enhanced encryption scheme (EFT).
- To introduce and analyze a novel distributed privacy mechanism using Laplace noise.
Main Methods:
- Studied existing security schemes: Shamir's secret sharing, perturbation-based, and various encryptions.
- Developed and integrated the enhanced encryption scheme (EFT).
- Implemented distributed Laplace (DLPA) and Geometric (DGPA) mechanisms for differential privacy, including diluted versions and noise from Gamma, Gauss, and Geometric distributions.
Main Results:
- The enhanced encryption scheme (EFT) is efficient and fault-tolerant.
- The proposed distributed privacy mechanism with Laplace noise (DLPA) achieves smaller redundant noise and improved efficiency.
- Experimental comparisons demonstrated the performance and scalability of implemented protocols.
Conclusions:
- The combination of the EFT security scheme and the Laplace DLPA mechanism provides the most efficient solution for secure distributed data aggregation with differential privacy.
- The study offers a comprehensive comparison of various security and privacy mechanisms in a practical setting.
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