CS-FLS:一种高效安全的云数据隐藏模型

CS-FLS: AN EFFICIENT AND SECURE CLOUD DATA HIDING MODEL

  • 摘要: 目前沙米尔秘密共享算法是一种经典的云数据隐私保护技术,但是该技术仍存在一些缺点,如:不能抵抗CSP的共谋攻击;使用该算法会造成较大的存储开销;随着数据量的增大,也会给用户带来较大的计算开销。针对这些问题,提出一种新的云数据隐藏方案,先使用FMSR编码对数据分块,初步隐藏数据的同时减少后续参与计算的数据块大小,从而减少存储开销和计算开销;使用LFSR算法生成伪随机数,将真实秘密转换成假秘密,从而抵抗共谋攻击;使用迭代多项式隐藏假秘密块。理论和安全分析表明,该方案能够降低存储开销并抵抗CSP共谋攻击,通过实验分析得出该方案可以降低用户的计算开销。

     

    Abstract: At present, Shamir secret sharing algorithm is a classic cloud data privacy protection technology, but this technology still has some shortcomings. It cannot resist the collusion attack of CSP. Using this algorithm will cause large storage overhead. As the amount of data increases, it will also bring users greater computing overhead. To solve these problems, a new cloud data hiding scheme is proposed. FMSR coding was used to block the data, initially hiding the data while reducing the size of data blocks involved in subsequent calculations, thereby reducing storage and computing costs. LFSR algorithm was used to generate pseudo-random numbers, and the real secret was converted into a false secret to resist collusion attacks. Iterative polynomial was used to hide pseudo secret blocks. Through theoretical and security analysis, the scheme can reduce storage overhead and resist CSP collusion attacks. Through experimental analysis, the proposed scheme can reduce user computing overhead.

     

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