Cognitive Radio Based System for Best Effort Communications in Sound-based Covert Channel for IoT Environments

Nowadays, the use of nodes with different sensing capabilities is pervasive. This leads to many environments capable of monitoring human activity for security, comfort, and connectivity applications among others. However, this also leads to many opportunities for security breaches in personal mobile devices when they are in such environments. In this work, we focus on a covert channel communication system based on sound waves with cognitive radio capabilities. In such system, the mobile nodes are infected with malware that allows the attacker to obtain information from the devices, sending data using a covert channel (hidden communications) to neighbor sensor nodes used for IoT applications through sound waves imperceptible to human ears. A cognitive radio design is based on allowing such hidden communications to occur when the primary channel is unused (i.e., when the user is not using or handling its device). As such, the primary network is considered to be any activity of the mobile (communication, application or service) and the secondary network is the covert channel communication system. Such a system is studied and mathematically analyzed using Continuous Time Markov Chains in order to obtain the throughput in the covert channel for different system parameters. A main result from this work is that, a careful selection of the activation parameter can lead to a more efficient covert data transfer system, irrespective of the rest of the system parameters.