Implementation of network information security monitoring system based on adaptive deep detection

Abstract

For a better detection in Network information security monitoring system, the author proposes a method based on adaptive depth detection. A deep belief network (DBN) was designed and implemented, and the intrusion detection system model was combined with a support vector machine (SVM). The data set adopts the NSL-KDD network communication data set, and this data set is authoritative in the security field. Redundant cleaning, data type conversion, normalization, and other processing operations are performed on the data set. Using the data conversion method based on the probability mass function probability mass function coding, a standard data set with low redundancy and low dimensionality can be obtained. Research indicates that when the batch size reaches 64, the accuracy of the test set reaches its maximum value. As the batch size increases, the accuracy first increases and then decreases. When the batch size continues to increase, the model will inevitably fall into the local optimal state, resulting in the degradation of the detection performance of the system. In terms of the false alarm rate, the DBN-SVM model is also the highest; however, it is only 10.73%. Under the premise of increasing the detection rate, the false alarm rate is improved; for the overall detection performance of the model, it is within an acceptable range. In terms of accuracy, the DBN-SVM model also scored the highest. The accuracy rate is the ratio of normal and correct classification for intrusion detection. It can explain the detection ability of the model. In summary, the overall detection ability of the DBN-SVM model is the best. The good classification ability to use SVM is proved, and the classification of low-dimensional features is expected to increase the detection rate of the system.

Computer Network Information Security and Protection Strategy Based on Big Data Environment

“…Currently, network attacks continuously beset the area of network information security, and network security incidents and accidents emerge endlessly. The impact of network information security varies over the individual, organizational, and social levels (Zhu, 2021;Niu et al, 2022). Worldwide, information virus attacks have repeatedly occurred in many countries, causing huge global economic losses.…”

Efficient Power Control for UAV Based on Trajectory and Game Theory

“…UAVs have the potential to either transport energy sources for wireless nodes or act as energy sources for wireless nodes themselves, so extending the lifespan of the network. Cable charging is incompatible with certain software platforms and networks, including the IoT and wireless sensor networks [10,11].…”