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In advanced jamming, the adversary intentionally concentrates the availableenergy budget on specific critical components (e.g., pilot symbols,acknowledgement packets, etc.) to (i) increase the jamming effectiveness, asmore targets can be jammed with the same energy budget; and (ii) decrease thelikelihood of being detected, as the channel is jammed for a shorter period oftime. One of the fundamental challenges in designing defense mechanisms againstan advanced jammer is understanding which jamming strategies yields the lowestthroughput, for a given channel condition and a given amount of energy. To thebest of our knowledge, this problem still remains unsolved. To fill this gap,in this paper we conduct a comparative analysis of several most viable advancedjamming schemes in the widely-used MIMO networks. We first mathematically modela number of advanced jamming schemes at the signal processing level, so that aquantitative relationship between the jamming energy and the jamming effect isestablished. Based on the model, theorems are derived on the optimal advancedjamming scheme for an arbitrary channel condition. The theoretical findings arevalidated through extensive simulations and experiments on a 5-radio 2x2 MIMOtestbed. Our results show that the theorems are able to predict jammingefficiency with high accuracy. Moreover, we show that the theorems can beincorporated to state-of-art reinforcement learning based jamming algorithmsand boost the action exploration phase so that a faster convergence isachieved.

Jam Sessions: Analysis and Experimental Evaluation of Advanced Jamming Attacks in MIMO Networks