Deep Learning-Based Network Data Security Analysis Research

With the continuous advancement of computer, microelectronics and wireless communication technologies, low-power sensor nodes that integrate various functions such as information acquisition, storage, processing and wireless communication in a tiny volume are rapidly developing. A wireless sensor network consists of a large number of inexpensive sensor nodes deployed in a monitoring area, forming a multi-hop network by means of self-organisation. The aim is to sense, collect and process information about the sensed objects in the coverage area and send it to the observer. Sensor networks have greatly changed the way humans interact with the outside world and improved their ability to understand the world, and can be widely used in national defence and military construction, industrial and agricultural production, environmental monitoring, medical care and other fields. In terms of data management and usage, it is generally accepted that the data collected by the nodes are transmitted directly to the base station or sink for processing and maintenance. However, it was found that this centralised approach to data management is bandwidth intensive, the aggregation point is prone to constitute a network bottleneck due to a single point of failure or attack, and lacks the practical deployment capability to accommodate the growth of sensor networks and some new applications.