Multi-network based MAC Protocol Identification with Decision Fusion

Abstract

Media access control (MAC) protocol identification is key to obtain the full awareness of wireless environments in both civil as well as military communications. In recent years, deep learning (DL) based MAC protocol identification has attracted great attention due to flourishing of deep neural networks (DNNs). However, existing research on DL based MAC protocol identification mostly exploits only one DNN to complete the identification task, which inevitably suffers from low identification accuracy. To combat the problem, this paper proposes a multi-network based algorithm that utilizes three DNNs, including a convolutional neural network (CNN), a long short-term memory (LSTM), and a gated recurrent unit (GRU), for MAC protocol identification. A decision fusion rule is adopted to fuse the individual results of three DNNs and make the final decision. Experiment results show that the proposed multi-network based algorithm performs better than the DL based methods using the single network.