Ultra-Wideband Channel State Information and Localization for Physical Layer Security

As an alternative to classical cryptography, Physical Layer Security (PhySec) provides primitives to achieve fundamental security goals like confidentiality, authentication or key derivation. Through its origins in the field of information theory, these primitives are rigorously analysed and their information theoretic security is proven. Nevertheless, the practical realizations of the different approaches do take certain assumptions about the physical world as granted.Many PhySec rely on the knowledge of Channel State Information (CSI) or of properties derived from CSI. Examples are wiretap codes and their respective design, key derivation based on reciprocal channel properties, and physical layer authentication. Despite the fact that many PhySec primitives rely on CSI knowledge for their functionality and security proofs, no definitive dataset is openly available that is suitable for verification and evaluation in practical scenarios. Different dataset are described for specific works, but none are released for public access.Hence, we aim to supply a dataset providing real world measurement of channel characteristics in relevant use case scenarios. With this dataset published here, we want to enable the research community to examine the underlying assumptions of PhySec in more detail, as well as provide a way to verify and support theoretical models and approaches with concrete data. This dataset consists of Ultra-Wideband (UWB) Channel State Information accompanied with the respective location information of the participating terminals. Since we additionally want to enable analysis with regard to security, two eavesdroppers are integrated in each measurement setup, whose observation is also recorded and provided. All measurements are conducted with consumer grade hardware to demonstrate the relevance for actual practical use case.To facilitate the unsupervised recording of measurements and thereby allow for long running measurements, we build an robot base moving autonomously within the measurement environment. Thereby, we were able to record measurements for about 112 hours, acquiring 1.2 million samples, making this dataset also suitable for machine learning methods.

作为古典密码学的替代方案，物理层安全（PhySec）提供了实现基本安全目标如保密性、认证或密钥派生的原语。这些原语源于信息理论领域，其信息论安全性得到了严格的验证。尽管如此，不同方法的实际实现确实基于对物理世界的某些假设。许多物理层安全方法依赖于信道状态信息（CSI）或由此信息派生的属性。例如，有窃听码及其相应的设计、基于互易信道属性的密钥派生以及物理层认证。尽管许多物理层安全原语依赖于CSI知识以实现其功能和安全证明，但至今尚无公开的、适用于实际场景验证和评估的权威数据集。虽然为特定工作描述了不同的数据集，但均未公开发布。因此，我们旨在提供一套数据集，该数据集提供了相关用例场景中信道特性的真实世界测量。本数据集在此发布，旨在使研究界能够更详细地检验物理层安全的潜在假设，并为理论模型和方法提供具体数据以进行验证和支持。本数据集包含超宽带（UWB）信道状态信息及其参与终端的相关位置信息。鉴于我们还想能够进行与安全相关的分析，每个测量配置中集成了两个窃听者，其观测结果也被记录并提供了。所有测量均使用消费级硬件进行，以展示其对于实际实际用例的相关性。为了便于无监督地记录测量，从而允许进行长时间运行测量，我们构建了一个能够在测量环境中自主移动的机器人平台。因此，我们能够记录约112小时的测量数据，获得120万个样本，使本数据集也适用于机器学习方法。