Ship information security risk detection based on data mining
Information security is the main cause of ship shipping safety risks.To ensure ship shipping safety,a ship in-formation security risk detection method based on data mining is designed.Using web crawler technology to collect basic ship information,network communication information,technical information,etc.,and implementing preprocessing such as cleaning,integration,and transformation of the information.Using correlation analysis method to extract ship information se-curity risk features,considering the temporal characteristics of the entire lifecycle of ship information,real-time transforma-tion processing is carried out on the extracted ship information security features.Using support vector machine models in data mining to construct a ship information security risk detection model,optimizing model parameters using the Dune Cat Swarm Algorithm.Simulation experiments show that this method can effectively obtain the information security risk detec-tion results of the research object,reduce the probability of various information security risk events by more than 70％,indic-ating that this method can effectively ensure the safety of ship navigation.
data miningship informationsecurity risk detectioncorrelation analysissupport vector machineparameter optimization
万方数据
维普
