基于随机森林的智慧城市信息安全风险预测

Risk Prediction of Smart City Information Security Based on Random Forest

智慧城市面临越来越严峻的信息安全威胁,传统的信息安全风险预测方法较难适应智慧城市信息安全的复杂性、非线性与不确定性等特性。本文通过改进现有智慧城市信息安全风险指标体系,基于机器学习中的随机森林算法,构建一个智慧城市信息安全风险预测模型,并与传统模型预测结果对比,结果表明,模型预测效果较其他模型更优秀。

The smart city is facing more and more severe threats of information security. The traditional information security risk prediction method is difficult to adapt to the smart city whose information securityhave complexity, nonlinear and uncertainty and other characteristics. In this paper,a smart city infformation security risk prediction model is construeted through improving the existed smart city information sellerity risk inedx system and based on a random forest algorithin of the machine learning. Furthmore,a result comparison with the traditional model is conducted. Results show that, the prediction of the model based on random forest is more outstanding.