Study of contextual channel characteristics in representative ad hoc networks. Due to the complexity of radio signal propagation, wireless communication channels are frequently subject to multi-path fading and interferences, and are sensitive to the surrounding environments. Although such dynamics of wireless channels introduce challenges to the efficiency and robustness of communications, they also provide unique sources ideal for bootstrapping security for communications due to the randomness and reciprocitiy properties of wireless channels under certain contexts [1]. To understand wireless channel properties under various real-world scenarios as well as their applicability to security bootstrapping, this work carries out extensive experiments under different types of ad hoc networks including body area networks and vehicular networks. Contextual factors such as indoor/outdoor locations, platform movements, interference from nearby environments and the type wireless radio are considered in the experiments [2].

Security bootstrapping exploiting contextual channel characteristics. Based on the contextual wireless characteristics, this work conducts preliminary research to explore the feasibility of bootstrapping wireless security in terms of device authentication, secret key generation, and the simultaneous execution of both. In order to minimize the assumption on the available hardware and out-of-band resources, this research aims to achieve the objectives based received signal strength (RSS) which can be conveniently available to most commodity wireless devices. Various powerful attacks such as man-in-the-middle (MITM) attacks are to be addressed in the research. Efficiency in terms of secret key generation rate is also studied in this work. Promising techniques such as collaborative security bootstrapping for simultaneous secret key generation and device athentication [3] are proposed and investigated.

Testbed and validation. This research implements testbed with a variety of commodity devices such as laptops, wireless sensors and smartphones to simulate real-world scenarios including body area networks and vehicular networks. The validation of the work considers various factors such as location and mobility of wireless devices.