Mobile communications are envisioned to be implemented in a large catalog of different applications: from traditional end-user services such as video streaming, to emerging digitalization solutions such as precision agriculture. Typically, mobile devices are considered powerful enough to execute all the modules and services required to support secure and broadband communications, but future scenarios require embedded devices as the primary hardware component. And those embedded devices are resource-constrained. Their limited computing power can only manage minimal communication services, excluding other additional functionalities as heavy security mechanisms. Lightweight security and encryption are the most adopted approaches to mitigate this problem, including stream cipher and chaotic cryptosystems. This is because those techniques are based on hardware elements and do not consume computational resources. But while software implementations are fully replicable with no error, hardware components may change their properties and behavior depending on the manufacturing techniques and design. For standard digital circuits, these small variations are not relevant, but chaotic cryptosystems are extremely sensitive, and the transmitter and the receptor are expected to be totally identical. However, this scenario prevents technological development, as all mobile embedded devices should be manufactured by the same industry agent to ensure interoperability. In this paper, we address this challenge and propose a universal receptor for chaotic cryptosystems in embedded mobile devices. The described receptor will be able to operate with transmitters based on any existing implementation of the Chua’s circuit. Using a combination of entropy metrics and binary distances, the receptor is able to identify the circuit implementation in the transmitter and dynamically adapt the receptor to this configuration. Simulation tools are used to validate the proposed technology, and the results show that interoperability errors are reduced by more than 63%.