  Modern Cyber-Physical Systems (CPSs) consist of numerous control units
interconnected by communication networks. Each control unit executes multiple
safety-critical and non-critical tasks in real-time. Most of the
safety-critical tasks are executed with a fixed sampling period to ensure
deterministic timing behaviour that helps in its safety and performance
analysis. However, adversaries can exploit this deterministic behaviour of
safety-critical tasks to launch inference-based-based attacks on them. This
paper aims to prevent and minimize the possibility of such timing inference or
schedule-based attacks to compromise the control units. This is done by
switching between strategically chosen execution rates of the safety-critical
control tasks such that their performance remains unhampered. Thereafter, we
present a novel schedule vulnerability analysis methodology to switch between
valid schedules generated for these multiple periodicities of the control tasks
in run time. Utilizing these strategies, we introduce a novel Multi-Rate
Attack-Aware Randomized Scheduling (MAARS) framework for preemptive
fixed-priority schedulers that minimize the success rate of
timing-inference-based attacks on safety-critical real-time systems. To our
knowledge, this is the first work to propose a schedule randomization method
with attack awareness that preserves both the control and scheduling aspects.
The efficacy of the framework in terms of attack prevention is finally
evaluated on several automotive benchmarks in a Hardware-in-loop (HiL)
environment.
