A belief rule base method for modeling latent states with uncertainty in Chrome extension risk assessment

作者：Xiao Cheng, Zihuang Cai, Zhi Wang, Yimeng Dong, Wanpeng Li · 发表于：Engineering Research Express · 年份：2026 · DOI：10.1088/2631-8695/ae62d1 · 研究领域：Physics

Chrome extensions, as popular browser functionality enhancement tools, often pose privacy risks due to permission-related issues. To address this, we propose a novel permission-based extension evaluation framework: RRIBRB-ExtPA (rule reduction based interval belief rule base for extension permission-based assessment, RRIBRB-ExtPA). This framework integrates our improved RRIBRB model. It reduces the dimension of precondition attributes. Rule combination and activation mechanisms are also optimized. Together, these improvements mitigate the rule explosion problem inherent in BRB models. Additionally, we introduce an overprivilege detection method to identify permission abuse behaviors in extensions, enhancing overall risk assessment capabilities. Experimental results demonstrate that RRIBRB-ExtPA maintains an accuracy rate of 98.6% even with an 87.5% reduction in the number of rules, while exhibiting stable performance under small-sample conditions. This indicates that RRIBRB-ExtPA is a viable permission-based extension risk assessment framework.