完美隐私的空中计算
Perfectly Private Over-the-Air Computation
AI总结：
研究如何在空中计算中实现完美隐私，通过结合实数域和模运算，解决隐私与计算精度的矛盾。
摘要：
本文研究了一个关键问题：如何在空中计算中实现完美隐私。实数域运算虽可逆但引入统计依赖导致隐私泄露，而模运算可去相关但非素数群下不可逆。通过巧妙利用实数域与模运算的交互，证明完美隐私与准确计算可同时实现，从而实现完美隐私聚合。
英文摘要：
This paper studies a key research question: how to achieve perfect privacy in over-the-air computation (AirComp)? The problem is particularly intriguing due to a dilemma. Real-field operations can ensure invertibility but generally introduce statistical dependence, resulting in inevitable privacy leakage. In contrast, modulo operations can decorrelate the output from the original message, but suffer from the ill-posed invertibility when applied over non-prime groups (e.g., the real field). This raises a subtle yet fundamental question: Does perfect privacy intrinsically conflict with AirComp? We show that the answer is no. By carefully leveraging the interplay between real-field and modulo operations, perfect privacy and accurate computation can, in fact, be achieved simultaneously, enabling perfectly private aggregation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
