Increasing base station anonymity using distributed beamforming

Advances in wireless communication technologies have enabled the networking of devices, which conventionally operated standalone, to form an Internet of Things (IoT). A typical network architecture consists of a set of data sources that report to a base station (BS), e.g., a data aggregation unit, over multi-hop paths. An example of such a network operation model includes surveillance of an unattended area using wireless sensor nodes, and advanced metering within a smart power grid. The unique role of the BS makes it a natural target for an adversary that desires to achieve the most impactful attack possible against an IoT network. Even if a network employs conventional security mechanisms such as encryption and authentication, an adversary may apply traffic analysis techniques to exploit unique traffic patterns within the network and ultimately identify the BS. The first step to successfully protect the BS from attack is to keep the BS’s identity, role, and location anonymous. This paper proposes a novel, cross-layer approach that boosts BS anonymity using distributed beamforming. We demonstrate that the characteristics of distributed beamforming make it extremely effective in improving BS anonymity in a wireless network while minimizing the amount of required communication energy overhead. Through analysis and simulation we demonstrate that the proposed approach is both efficient and effective at countering an adversary that employs evidence theory analysis to locate the BS.