Digital Library Network Anomaly Detection System based on Situation Awareness

The cloud computing platform of the smart library is designed to achieve functions such as collecting, transmitting, processing, and storing massive data. In order to ensure the normal operation of the smart library business application system, cloud computing architecture is generally adopted. Cloud computing data centers carry massive amounts of data and network devices, and the massive data information accumulated during their storage and transmission processes may be destroyed. Once attacked, the consequences would be very serious. Meanwhile, cloud computing and virtualization technologies pose new challenges to the security of smart library data centers. Traditional information security defense systems can no longer meet the security protection requirements of smart libraries for information systems. Therefore, in order to ensure the information security of smart libraries, it is necessary to break through the shortcomings of existing information security defense systems and provide effective support for them. Therefore, this article explored a network anomaly situation awareness model based on PCA-BP algorithm to detect the abnormal status of digital library networks. The experimental results showed that when DOS attack was used in the experiment, the prediction accuracy of the BP algorithm model was 0.883, while the prediction accuracy of the PCA-BP (Principal Component Analysis-Back Propagation) algorithm was 0.94.