Traffic statistics of wireless networks, e.g. flow packet rates, packet sizes, and packet timing information, can reveal important information of the network and its users. Therefore, it is important to understand the confidentiality of traffic statistics in the presence of intelligent eavesdroppers. In this thesis, we consider the problem of estimating flow packet rates in CSMA/CA networks using only passive over-the-air signal observation from a single eavesdropper. We assume that the eavesdropper does not know the network topology and hence the contention graph indicating the interference pattern. Additionally, if the eavesdropped network permits spatial reuse, then there will be collisions at the eavesdropper, leading to partial measurements. We propose a flow packet rate estimation algorithm that leverages the time reversibility of the traffic on networks with single-hop flows. We prove that the estimated flow packet rates converge to the true values almost surely, and demonstrate the performance of the algorithm in NS-3 simulated networks with practical CSMA/CA protocol setup. Our results show that single-hop-flow CSMA/CA networks are fundamentally vulnerable to traffic packet rate eavesdropping, and thus future research in improving traffic statistics privacy are critically needed.