Xuran Li

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The security and privacy of underwater acoustic sensor networks has received extensive attention recently due to the proliferation of underwater activities. This paper proposes an analytical model to investigate the eavesdropping attacks in underwater acoustic sensor networks. Our analytical framework considers the impacts of various underwater acoustic(More)
Underwater Acoustic Sensor Networks (UWASNs) have the wide of applications with the proliferation of the increasing underwater activities recently. Most of current studies are focused on designing protocols to improve the network performance of WASNs. However, the security of UWASNs is also an important concern since malicious nodes can easily wiretap the(More)
Wireless sensor networks (WSNs) play an important role in Cyber Physical Social Sensing (CPSS) systems. An eavesdropping attack is one of the most serious threats to WSNs since it is a prerequisite for other malicious attacks. In this paper, we propose a novel anti-eavesdropping mechanism by introducing friendly jammers to wireless sensor networks (WSNs).(More)
Context identifying based on speech data is important to social services and city management. In a complex application environment, a speech recognition system needs to address two main problems: background noises and large vocabulary search latency. We use the adjustment acoustic model to deal with the scenario adaptation, and we use adjustment dictionary(More)
This paper investigates the eavesdropping attacks in underwater acoustic networks (UANets). In particular, we propose an analytical framework to model the eavesdropping attacks in UANets in terms of the eavesdropping probability. Results of extensive simulations match the analytical results, indicating the effectiveness and accuracy of our model. Besides,(More)