论文标题
物联网中的多方计算用于隐私保护
Multi-Party Computation in IoT for Privacy-Preservation
论文作者
论文摘要
隐私保护一直是对物联网辅助智能系统及其无处不在的智能传感器的日益严重关注的问题。为了解决问题，正在培训智能系统以更多地依赖聚合数据，而不是直接使用原始数据。但是，大多数现有的保护隐私数据聚合的策略都取决于基于计算密集型的同型加密操作或通信密集型协作机制。不幸的是，这些方法都不适用于资源约束的物联网系统。在这项工作中，我们利用基于交流的通信技术有效地实现了基于多方计算（MPC）的策略，即著名的Shamir的秘密共享（SSS），并优化了相同的功能，以使其适合于现实世界中的物联网系统。
Preservation of privacy has been a serious concern with the increasing use of IoT-assisted smart systems and their ubiquitous smart sensors. To solve the issue, the smart systems are being trained to depend more on aggregated data instead of directly using raw data. However, most of the existing strategies for privacy-preserving data aggregation, either depend on computation-intensive Homomorphic Encryption based operations or communication-intensive collaborative mechanisms. Unfortunately, none of the approaches are directly suitable for a resource-constrained IoT system. In this work, we leverage the concurrent-transmission-based communication technology to efficiently realize a Multi-Party Computation (MPC) based strategy, the well-known Shamir's Secret Sharing (SSS), and optimize the same to make it suitable for real-world IoT systems.
