Research on Network Security Risk Assessment and Forecasting Model for Tobacco Information Systems

Tobacco information systems network security risk assessment and prediction models include the establishment of Design for Six Sigma (DFSS) process-based network security risk assessment model and a semi-supervised classification learning-based network security risk prediction model. The calculation of information systems network security risk value includes two parts: asset value and risk factors. The network security risk assessment uses the failure mode and effects analysis (FEMA) method to identify the key influence factors (CTQ) based on the identified asset value and risk factors evaluation. At the same time, in ordering to discover potential network security risk factors, a semi-supervised classification learning algorithm is used to establish a network information security risk prediction model. The key impact factors identified and the potential impact factors analyzed are mined, technical measures and management measures are adopted to strengthen security. The evaluation and verification results show that through the improvement of the identified key influencing factors and potential influencing factors, 17 non-compliances and 2 weak-compliances in the evaluation indicators have been completely resolved. And the ability to prevent network information security risks has also been effectively improved.