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基于LWE的高效身份基分級加密方案

發(fā)布時間:2018-08-18 14:07
【摘要】:格上可固定維數(shù)陷門派生的身份基分級加密(hierarchical identity-based encryption,HIBE)體制,因其具有在陷門派生前后格的維數(shù)保持不變的特性而受到廣泛關(guān)注,但這種體制普遍存在陷門派生復(fù)雜度過高的問題.針對這一問題,分別給出隨機(jī)預(yù)言模型和標(biāo)準(zhǔn)模型下的改進(jìn)方案.首先利用MP12陷門函數(shù)的特性提出一種優(yōu)化的Zq可逆矩陣提取算法,再基于該優(yōu)化算法結(jié)合固定維數(shù)的陷門派生算法和MP12陷門函數(shù)完成方案的建立和陷門派生階段,然后與對偶Regev算法相結(jié)合完成隨機(jī)預(yù)言模型下HIBE方案的構(gòu)造.并且利用二進(jìn)制樹加密系統(tǒng)將該方案改進(jìn)為標(biāo)準(zhǔn)模型下的HIBE方案.兩方案安全性均可歸約至LWE問題的難解性,其中隨機(jī)預(yù)言模型下的方案滿足適應(yīng)性安全,而標(biāo)準(zhǔn)模型下的方案滿足選擇性安全,并給出嚴(yán)格的安全性證明.對比分析表明:在相同的安全性下,隨機(jī)預(yù)言模型下的方案較同類方案在陷門派生復(fù)雜度方面顯著降低,而標(biāo)準(zhǔn)模型下的方案是同類最優(yōu)方案的1/6,且格的維數(shù)、陷門尺寸和密文擴(kuò)展率等參數(shù)均有所降低,計算效率明顯優(yōu)化.
[Abstract]:The hierarchical identity-based encryption hierarchical encryption (HIBE) system with fixed dimension on the lattice has been widely concerned because of its invariable dimension before and after the trapping school students. However, the complexity of the trapping school students is generally too high in this system. In order to solve this problem, the improved schemes under stochastic prophecy model and standard model are given respectively. Based on the MP12 trapdoor function, an optimized Zq reversible matrix extraction algorithm is proposed. Based on this algorithm, the trapdoor generation algorithm with fixed dimension and the MP12 trapdoor function are used to complete the scheme and the trapping gate generation stage. Then combined with dual Regev algorithm, the construction of HIBE scheme under stochastic prediction model is completed. And the binary tree encryption system is used to improve this scheme to HIBE scheme under the standard model. The security of the two schemes can be reduced to the insolvability of the LWE problem, in which the scheme under the stochastic prediction model satisfies the adaptive security, while the scheme under the standard model satisfies the selective security, and the strict security proof is given. The comparative analysis shows that under the same security, the scheme under the stochastic prediction model is significantly lower than the similar scheme in terms of the complexity of the trapping scheme, while the scheme under the standard model is 1 / 6 of the optimal scheme of the same kind and the dimension of the lattice. The trapdoor size and ciphertext expansion rate are reduced, and the computational efficiency is optimized.
【作者單位】: 河南理工大學(xué)計算機(jī)科學(xué)與技術(shù)學(xué)院;
【基金】:國家自然科學(xué)基金項目(61300216) 河南省科技廳基礎(chǔ)與前沿技術(shù)研究計劃項目(142300410147) 河南省教育廳自然科學(xué)研究項目(12A520021);河南省教育廳高等學(xué)校重點科研項目(16A520013)~~
【分類號】:TP309.7

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本文編號:2189705


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