Wireless Modulation Identification: Filling the Gap in IoT Networks Security Audit

The massive deployment of IoT devices comes with the creation of many wireless communication protocols designed to support various applications. However, while some of these protocols are public and widely used, such as Bluetooth Low Energy or Enhanced ShockBurst, the specifications of other protocols are only partially, if at all, publicly available, making it difficult for security researchers to study them, especially for auditing purposes. In this paper, we address this issue by presenting an innovative, easy-to-use and protocol-agnostic toolkit to analyze unknown network communications. The toolkit is designed to automatically infer their physical layer characteristics and to extract the binary content of their frames. We conducted experiments to identify the modulation parameters for various wireless communications used by off-the-shelf devices as well as for randomly generated protocols, considering both FSK and ASK modulations. In addition, our results show that the proposed toolkit is capable of successfully detecting covert channels in wireless environments. We also conducted a case study on an undocumented proprietary wireless mouse protocol.