Decentralized Covert Routing in Heterogeneous Networks Using Reinforcement Learning

arXiv:2402.10087v1 Announce Type: cross
Abstract: This letter investigates covert routing communications in a heterogeneous network where a source transmits confidential data to a destination with the aid of relaying nodes where each transmitter judiciously chooses one modality among multiple communication modalities. We develop a novel reinforcement learning-based covert routing algorithm that finds a route from the source to the destination where each node identifies its next hop and modality only based on the local feedback information received from its neighboring …

abstract algorithm arxiv communication communications cs.lg cs.ni data decentralized eess.sp multiple network networks nodes novel reinforcement reinforcement learning routing type