Kangbao County is located in the northwest of Bashang in Hebei Province,which is a sub-arid area in the middle temperate zone,with a cold and arid climate and frequent disastrous weather.The meteorological data of Kan...Kangbao County is located in the northwest of Bashang in Hebei Province,which is a sub-arid area in the middle temperate zone,with a cold and arid climate and frequent disastrous weather.The meteorological data of Kangbao County Meteorological Station from 1994 to 2023 were selected,and the meteorological elements such as air pressure,temperature,precipitation,wind,relative humidity,sunshine,thunderstorm,hail,gale,rainstorm,fog,and snow cover were counted.The climate background analysis and high-impact weather analysis were carried out in combination with the topographic characteristics,geographical location,and climate characteristics.The results of meteorological sensitivity survey in the park showed that industries such as food,agriculture and new energy are very sensitive to temperature.During the visit to the enterprises in the park,it was found that heavy precipitation,snow,strong winds and hail had a great impact on many industries,and it was recommended to carry out long-term planning and reasonable design of buildings.It should pay close attention to forecasts and early warnings,formulate emergency plans for high-impact weather defense,and actively take preventive measures.展开更多
When Internet of Things(IoT)nodes access the network through wireless channels,the network is vulnerable to spoofing attacks and the Sybil attack.However,the connection of massive devices in IoT makes it difficult to ...When Internet of Things(IoT)nodes access the network through wireless channels,the network is vulnerable to spoofing attacks and the Sybil attack.However,the connection of massive devices in IoT makes it difficult to manage and distribute keys,thus limiting the application of traditional high-level authentication schemes.Compared with the high-level authentication scheme,the physical layer authentication scheme realizes the lightweight authentication of users by comparing the wireless channel characteristics of adjacent packets.However,traditional physical layer authentication schemes still adopt the one-to-one authentication method,which will consume numerous network resources in the face of large-scale IoT node access authentication.In order to realize the secure access authentication of IoT nodes and regional intrusion detection with low resource consumption,we propose a physical layer authentication mechanism based on convolution neural network(CNN),which uses the deep characteristics of channel state information(CSI)to identify sending nodes in different locations.Specifically,we obtain the instantaneous CSI data of IoT sending nodes at different locations in the pre-set area,and then feed them into CNN for training to procure a model for IoT node authentication.With its powerful ability of data analysis and feature extraction,CNN can extract deep Spatio-temporal environment features of CSI data and bind them with node identities.Accordingly,an authentication mechanism which can distinguish the identity types of IoT nodes located in different positions is established to authenticate the identity of unknown nodes when they break into the pre-set area.Experimental results show that this authentication mechanism can still achieve 94.7%authentication accuracy in the case of a low signalto-noise ratio(SNR)of 0 dB,which means a significant improvement in authentication accuracy and robustness.展开更多
文摘Kangbao County is located in the northwest of Bashang in Hebei Province,which is a sub-arid area in the middle temperate zone,with a cold and arid climate and frequent disastrous weather.The meteorological data of Kangbao County Meteorological Station from 1994 to 2023 were selected,and the meteorological elements such as air pressure,temperature,precipitation,wind,relative humidity,sunshine,thunderstorm,hail,gale,rainstorm,fog,and snow cover were counted.The climate background analysis and high-impact weather analysis were carried out in combination with the topographic characteristics,geographical location,and climate characteristics.The results of meteorological sensitivity survey in the park showed that industries such as food,agriculture and new energy are very sensitive to temperature.During the visit to the enterprises in the park,it was found that heavy precipitation,snow,strong winds and hail had a great impact on many industries,and it was recommended to carry out long-term planning and reasonable design of buildings.It should pay close attention to forecasts and early warnings,formulate emergency plans for high-impact weather defense,and actively take preventive measures.
基金This work was supported by National Natural Science Foundation of China(No.61871404,61801435).
文摘When Internet of Things(IoT)nodes access the network through wireless channels,the network is vulnerable to spoofing attacks and the Sybil attack.However,the connection of massive devices in IoT makes it difficult to manage and distribute keys,thus limiting the application of traditional high-level authentication schemes.Compared with the high-level authentication scheme,the physical layer authentication scheme realizes the lightweight authentication of users by comparing the wireless channel characteristics of adjacent packets.However,traditional physical layer authentication schemes still adopt the one-to-one authentication method,which will consume numerous network resources in the face of large-scale IoT node access authentication.In order to realize the secure access authentication of IoT nodes and regional intrusion detection with low resource consumption,we propose a physical layer authentication mechanism based on convolution neural network(CNN),which uses the deep characteristics of channel state information(CSI)to identify sending nodes in different locations.Specifically,we obtain the instantaneous CSI data of IoT sending nodes at different locations in the pre-set area,and then feed them into CNN for training to procure a model for IoT node authentication.With its powerful ability of data analysis and feature extraction,CNN can extract deep Spatio-temporal environment features of CSI data and bind them with node identities.Accordingly,an authentication mechanism which can distinguish the identity types of IoT nodes located in different positions is established to authenticate the identity of unknown nodes when they break into the pre-set area.Experimental results show that this authentication mechanism can still achieve 94.7%authentication accuracy in the case of a low signalto-noise ratio(SNR)of 0 dB,which means a significant improvement in authentication accuracy and robustness.
