Covert Wireless Communications with Active Eavesdropper on AWGN Channels
This addresses security vulnerabilities in wireless networks for scenarios with adaptive eavesdroppers, offering practical countermeasures.
The paper tackles the problem of covert wireless communication against an active eavesdropper who dynamically adjusts detection, finding that the square root law fails and Alice cannot hide transmissions without prior knowledge, but proposes a randomized scheduling method that allows covert transmission if probability is below a threshold and a density-based routing scheme for multi-hop networks.
Covert wireless communication can prevent an adversary from knowing the existence of user's transmission, thus provide stronger security protection. In AWGN channels, a square root law was obtained and the result shows that Alice can reliably and covertly transmit $\mathcal{O}(\sqrt{n})$ bits to Bob in n channel uses in the presence of a passive eavesdropper (Willie). However, existing work presupposes that Willie is static and only samples the channels at a fixed place. If Willie can dynamically adjust the testing distance between him and Alice according to his sampling values, his detection probability of error can be reduced significantly via a trend test. We found that, if Alice has no prior knowledge about Willie, she cannot hide her transmission behavior in the presence of an active Willie, and the square root law does not hold in this situation. We then proposed a novel countermeasure to deal with the active Willie. Through randomized transmission scheduling, Willie cannot detect Alice's transmission attempts if Alice can set her transmission probability below a threshold. Additionally, we systematically evaluated the security properties of covert communications in a dense wireless network, and proposed a density-based routing scheme to deal with multi-hop covert communication in a wireless network. As the network grows denser, Willie's uncertainty increases, and finally resulting in a "shadow" network to Willie.