基于容错学习的属性基加密方案的具体安全性分析

为了能全面研究基于容错学习(LWE)的属性基加密(ABE)方案的安全性，考察其抵抗现有攻击手段的能力，在综合考虑格上算法和方案噪声扩张对参数的限制后，利用已有的解决LWE的算法及其可用程序模块，该文提出了针对基于LWE的ABE方案的具体安全性分析方法。该方法可以极快地给出满足方案限制要求的具体参数及方案达到的安全等级，此外，在给定安全等级的条件下，该方法可以给出相应的具体参数值。最后，利用该方法分析了4个典型的基于LWE的属性基加密方案的具体安全性。实验数据表明，满足一定安全等级的基于LWE的属性基方案的参数尺寸过大，还无法应用到实际中。

Analysis Method for Concrete Security of Attribute-based Encryption Based on Learning With Errors

In order to comprehensively study the security of the Attribute-Based Encryption (ABE) scheme based on Learning With Errors (LWE) and test its ability to resist existing attacks, an analysis method for concrete security of ABE based on LWE is proposed. After consideration of the parameter restrictions caused by algorithms on lattices and noise expansion, this method applies the existing algorithms to solving LWE and the available program modules, and it can quickly provide the specific parameters that satisfy the scheme and estimate the corresponding security level. In addition, it can output the specific parameters that satisfy the pre-given security level. Finally, four existing typical schemes are analyzed by this method. Experiments show that the parameters are too large to be applied to practical applications.