Jamming-resistant rate adaptation in Wi-Fi networks

We introduce a theoretical framework to formally analyze the vulnerability of IEEE 802.11 rate adaptation algorithms (RAAs) to selective jamming attacks, and to develop countermeasures providing provable performance guarantees. Thus, we propose a new metric called Rate of Jamming (RoJRoJ), wherein a low RoJRoJ implies that an RAA is highly vulnerable to jamming attacks, while a high RoJRoJ implies that the RAA is resilient. We prove that several state-of-the-art RAAs, such as ARF and SampleRate, have a low RoJRoJ (i.e.,  10%10% or lower). Next, we propose a robust RAA, called Randomized ARF (RARF). Using tools from renewal theory, we derive a closed-form lower bound on the RoJRoJ of RARF. We validate our theoretical analysis using ns-3 simulations and show that the minimum jamming rate required against RARF is about 33%33% (i.e., at least three times higher than the RoJRoJ of other RAAs).