Abstract
Smartphone reconnaissance, the first step to launch security attacks to a target smartphone, enables an adversary to tailor attacks by exploiting the known vulnerabilities of the target system. In this paper we investigate smartphone OS identification with encrypted traffic. We propose four algorithms to do that, which are based on the spectral analysis of the encrypted traffic. The algorithms are designed for high identification accuracy by removing noise frequency components and for high efficiency in terms of computation complexity. We evaluate the identification algorithms with smartphone traffic collected over three months. The experiment results show that the algorithms can identify the smartphone OS accurately. The identification accuracy can reach 100% with only 30 seconds of smartphone traffic.
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