Online Schedule Randomization to Mitigate Timing Attacks in 5G Periodic URLLC Communications

Abstract

Ultra-reliable low-latency communication (URLLC) in 5G networks is designed to support time-critical applications such as industrial control systems (ICSs), where user equipment (UEs) communicate with a base station (BS) with very high reliability and low latency. Most of these communications in ICSs are periodic and associated with hard deadlines. To provide a reliable service while satisfying the hard deadlines, the BS usually reserves slots and frequencies and precomputes the schedule for such UEs. The same schedule repeats over time, which makes the slots and frequencies predictable. However, an attacker can exploit this aspect and launch timing attacks disrupting specific communication, thereby, undermining the safety of the system. To mitigate such attacks, we present an online strategy that randomizes the scheduled slots and frequencies over time without violating the flow deadlines. We use Kullback-Leibler divergence to measure the randomness in the schedules generated by our strategy with reference to a hypothetical truly random strategy. We perform security analysis of our proposed strategy using Prediction Probability to measure the predictability in the slots of the generated schedules. We evaluate the performance of our strategy against a state-of-the-art baseline, and show that our strategy performs better than the baseline across all parameter settings.