A New Covert Channel in Fixed-Priority Real-Time Multiframe Tasks

This study investigates the presence of illicit information flows in fixed-priority multiframe real-time systems. We identify an algorithmic covert channel (called FrameLeaker) that enables a low-priority task to deduce the execution patterns (frames) of a high-priority task. We show that the response time of a targeted low-priority task (receiver) can be used to extract the execution behavior of a high-priority task (sender). We further introduce a metric called "inference precision ratio" to evaluate the efficacy of the received information.