Sensitive information leakage awareness method for big data platform based on multi-attributes decision-making and taint tracking - Le-tian SHA; Fu XIAO; Wei CHEN; Jing SUN; Ru-chuan WANG (Tongxin xuebao)
Based on multiple-attribute-decision-making and taint tracking,a sensitive-information leakage awareness method was proposed,some relative known vulnerabilities in big data platform was analyzed,target database was extracted and extended,multiple attribute model was built combined with operation semantic,a grey-correlation-analysis and technique for order preference by similarity to an ideal solution based sensitivity measurement was designed in combination of regular operation semantic for sensitive information.A prototype was built based on taint tracking,sensitive-information leakage vulnerabilities could be verified and discovered across big data platforms in this method.The experiment shows that verification for known bugs and discovery for unknown vulnerabilities can be accomplished based on leakage scenarios,which can be regarded as a support for protection in dynamic sensitive information data flow.