EARS: Cloud-based Oblivious Spectrum Mapping and Allocation

动态频谱接入（DSA）技术提供了更有效地利用无线电频谱的潜力，它允许无线电感知哪些部分的无线电频谱目前没有被许可用户或其他机会主义用户使用。然而，由于无线电传播环境的随机性和无线电信号可以在非常低的功率水平下接收，因此在特定频段检测传输的存在是困难的。通过收集和处理来自多个无线电的传感信息，可以使无线电频谱的传感更加准确。然而，在合并这些信息时，感应无线电的位置和特征可能会透露给其他无线电或参与收集和合并信息的各种公司。该研究项目将开发新技术，以保护作为DSA系统一部分的无线电频谱传感用户的隐私。这些技术构建在安全计算原语（例如乱码电路）之上，乱码电路使用加密技术允许用户计算结果，而任何一方都无法知道另一方的计算输入。尽管在频谱传感系统中不可能实现完全隐私，但该项目旨在开发实现k-匿名的系统，其中用户的位置和功能可能只减少到k种可能性中的一种。开发此类技术的一个重大挑战是，许多安全计算原语需要很高的计算复杂性，因此不能在许多DSA设备上实现，例如未来几代的蜂窝电话。因此，该项目将开发具有足够低复杂性的隐私保护频谱传感技术，以在此类设备上实现。实现这一目标的方法之一是在设备和云计算服务器之间划分计算。这些技术将在软件定义的无线电试验台上实现，该试验台与商业云计算资源接口，允许使用真实无线电信号和真实计算平台进行测试。

Dynamic spectrum access (DSA) techniques offer the potential to use the radio spectrum more efficiently by allowing radios to sense which parts of the radio spectrum are not currently being used by the licensed users or other opportunistic users. However, detecting the presence of transmissions in a particular band is difficult because of randomness in the radio propagation environment and because radio signals can be received at very low power levels. Sensing the radio spectrum can be made more accurate by collecting and processing the sensing information from multiple radios. However, in combining this information, the locations and characteristics of the sensing radios may be revealed to the other radios or to various companies involved in collecting and combining the information. This research project will develop novel techniques to protect the privacy of users involved in sensing the radio spectrum as part of a DSA system. The techniques are built on top of secure computing primitives, such as garbled circuits, which uses cryptographic techniques to allow users to compute a result without any of the parties being able to know the other parties inputs to the computation. Although complete privacy is not possible in a spectrum sensing system, this project aims to develop systems that achieve k-anonymity, in which a user's location and capabilities may only be reduced to one of k possibilities. A significant challenge in developing such techniques is that many secure computing primitives require high computational complexity, and thus cannot be implemented on many DSA devices, such as future generations of cellular phones. Thus, the project will develop privacy-preserving spectrum sensing techniques that have sufficiently low complexity to be implemented on such devices. One of the approaches to achieving this is to partition the computation between the devices and a cloud-computing server. These techniques will be implemented on a software-defined radio testbed that interfaces with a commercial cloud computing resource to allow testing using real radio signals and real computing platforms.