In this paper, we devised a combined approach to distinguish different types of jamming attacks against wireless networks. Based on the shared characteristics of the wireless medium, a wireless network can be easily affected by jamming attacks, which is one of the most effective forms of denial-of-service (DoS) attacks against this type of networking architecture. Attacks can be implemented by either corrupting the operations of the medium access control (MAC) protocols or transmitting large amounts of interfering wireless signals without obeying the MAC protocols. Most jamming detection approaches cannot provide an effective way for differentiating between the various categories of jamming attacks. To enable the network to perform defense strategies more effectively, distinguishing the type of different jamming attacks is necessary. In this paper, we improve existing jamming detection approaches by using a novel statistical model and evaluate it both theoretically and experimentally. We begin by combining two existing jamming detection methods together to sort the jamming types roughly. Then, based on the statistical data of Packets Send Ratio (PSR) and Packets Delivery Ratio (PDR) in different jamming situations, we built a model to further subdivide the jamming attacks. Finally, we evaluate our proposed strategy using the ns-2 simulation platform.
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