Concerning the problem that destruction of nodes or edges in coal transportation road network for emergencies has caused problems in blockage of coal transportation road networks, based on complex network theory, the network models constructed by original method and dual method were established, and their reliability were simulated by Matlab software. Firstly, basic characteristics of two networks were compared and analyzed, and then relative changes of network efficiency were proposed to identify key road segments in network. Based on this, a network reliability evaluation model was established, and three reliability evaluation indexes including network efficiency, maximum connected subgraph relative size and network dispersion were proposed to simulate network reliability under two destruction modes:random destruction and deliberate destruction. The experimental result shows that in deliberate destruction mode, when 10% of nodes fail, three reliability index values are 10%, 20%, and 20, respectively, while the index values in random destruction mode still maintain at a high level. Therefore, the coal transportation network is robust to random destruction and vulnerable to deliberate destruction. The protection of important nodes in network should be strengthened.

Heterologous splicing is a typical tampering behavior for digital voice. It mainly uses the audio editing software to splice the voice clips recorded in different scenes, so as to achieve the purpose of changing the semantics of voice. Considering the difference of background noise in different scenes, a tampering detection algorithm based on noise consistency for digital voice heterologous splicing was proposed. Firstly, the Time-Recursive Averaging (TRA) algorithm was applied to extract the background noise contained in the voice to be detected. Then, the Change-Point Detection (CPD) algorithm was used to detect whether abrupt changes existed in the noise variance, which was used to determine whether the voice was tampered, and to locate the tampering position of the testing voice. The experimental results show that the proposed algorithm can achieve good performance in detecting the tampering position of heterologous splicing for digital voice.