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Recent experimental studies reveal that several well-known and widely deployed Rate Adaptation Algorithms (RAAs) in 802.11 WLANs are vulnerable to selective jamming attacks. However, previous work resorts to complex jamming strategies that are hard to implement and does not provide applicable solutions to this problem. In this paper, the authors analyze the vulnerabilities of existing RAAs to simple jamming attacks and propose judicious use of randomization to address this problem. They introduce a theoretical framework based on a bursty periodic jamming model to analyze the vulnerabilities of popular RAAs, such as ARF and SampleRate. Their parameterized analysis shows that a jamming rate of 10% or below is sufficient to bring the throughput of these algorithms below the base rate of 1 Mb/s.
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