Research on the Application Strategy of Artificial Intelligence in Cyberspace Security

Behind the wide application of digital information technology, the security problem of cyberspace also follows. In the face of increasingly complex and changeable cyber attacks and persistent cyber attacks, the traditional cyberspace security defense technology can only respond passively, and its defense effect has certain limitations. In this regard, based on the actual application requirements, this paper will deeply explore the application strategy of artificial intelligence technology in improving cyberspace security, and focus on constructing a situation prediction model from the perspective of cyberspace security situation awareness, which provides strong support for network defense. Practice has proved that using the long-term and short-term memory network (LSTM) to build a situation prediction model can capture the long-term dependence in time series data such as network traffic and logs, and achieve the purpose of improving the accuracy of cyberspace security situation prediction. The introduction of genetic algorithm (GA) can further optimize the setting of parameters, strengthen the prediction accuracy and overall performance of LSTM, so as to promote the transformation and upgrading of cyberspace security defense technology.