fixed interval is bounded. In [@ahmetifacwc2017], we used an SINR-based probabilistic model to investigate a discrete-time networked stabilization problem for scenarios where there is no disturbance, but a jamming attacker can jam the wireless channel at each time instant with a different interference power level that is unknown a priori. Our results in [@ahmetifacwc2017] indicate that stabilization can be achieved if the average interference power is bounded in the long run even if the power can be very large at certain times.

In this paper we consider situations where the jamming attacker can strategically change the interference levels at each time, as in [@ahmetifacwc2017]. However, differently from [@ahmetifacwc2017], we now consider disturbance, and through stochastic analysis, we show that when the dynamics is subject to disturbance, jamming attacks can potentially become more dangerous. Our results indicate that a strategic attacker may take advantage of the disturbance to cause instability even if the attacked system without disturbance is stable. Specifically, the attacker can cause the state norm to grow to arbitrarily large values with arbitrarily high probabilities, while keeping the average jamming interference power below a threshold in the long run. Thus, as in the deterministic case discussed in [@de2015inputtran], a 