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 ( R o J ), wherein a low R o J implies that an RAA is highly vulnerable to jamming attacks, while a high R o J implies that the RAA is resilient. We prove that several state-of-the-art RAAs, such as ARF and SampleRate, have a low R o J (i.e.,  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 R o J of RARF. We validate our theoretical analysis using ns-3 simulations and show that the minimum jamming rate required against RARF is about 33 % (i.e., at least three times higher than the R o J of other RAAs).