Key space.

The unique infinite self-renewal ability and multidirectional differentiation potential of stem cells provide a strong support for the clinical treatment. In light of the growing demands for stem cell storage, how to ensure personal privacy security and comply with strict ethical supervision requirements is particularly important. In order to solve the problem of low security of traditional encryption algorithm, we proposed a double encryption protection (DEP) algorithm for stem cell bank privacy data based on improved AES and chaotic encryption technology. Firstly, we presented the hash value key decomposition algorithm, through the hash value dynamic coding, cyclic shift, conversion calculation to get the key of each subsystem in the built algorithm. Secondly, DEP algorithm for privacy data is realized with two level of encryption. The first level of encryption protection algorithm used AES as the main framework, adding dynamic coding and byte filling based on DNA coding, and carries out dynamic shift of rows and simplified mixing of columns. The second level of encryption protection algorithm conducted random encoding, operation, diffusion and decoding based on the results of our proposed sequence conversion algorithm. Finally, we raised two evaluation indexes, the number of characters change rate (NCCR) and the unified average change intensity of text (UACIT) to measure the sensitivity of encryption algorithms to changes in plain information. The experimental results of using DEP shown that the average values of histogram variance, information entropy, NCCR and UACIT are116.7883, 7.6688, 32.52% and 99.67%, respectively. DEP algorithm has a large key space, high key sensitivity, and enables dynamic encryption of private data in stem cell bank. The encryption scheme provided in this study ensures the security of the private information of stem cell bank in private cloud environment, and also provides a new method for the encryption of similar high confidentiality data.

干细胞的独特无限自我更新能力与多向分化潜能，为临床治疗提供了坚实支撑。随着干细胞存储需求的日益增长，如何保障个人隐私安全并符合严格的伦理监管要求显得尤为重要。为解决传统加密算法安全性较低的问题，本研究提出了一种基于改进高级加密标准（Advanced Encryption Standard, AES）与混沌加密技术的干细胞库隐私数据双加密保护（Double Encryption Protection, DEP）算法。
首先，本文提出哈希值密钥分解算法，通过对哈希值进行动态编码、循环移位与转换计算，得到所构建算法中各子系统的密钥。其次，隐私数据双加密保护算法通过两级加密流程得以实现：第一级加密保护算法以AES为核心框架，新增基于DNA编码的动态编码与字节填充操作，并对行进行动态移位、对列进行简化混合运算；第二级加密保护算法基于本文提出的序列转换算法结果，开展随机编码、运算、扩散与解码操作。
最后，本文提出两项评估指标：字符变化率（Number of Characters Change Rate, NCCR）与文本统一平均变化强度（Unified Average Change Intensity of Text, UACIT），用于衡量加密算法对明文信息变化的敏感性。采用DEP算法开展的实验结果表明，直方图方差、信息熵、NCCR以及UACIT的平均值分别为116.7883、7.6688、32.52%与99.67%。DEP算法密钥空间大、密钥敏感性高，可实现干细胞库隐私数据的动态加密。本研究提出的加密方案既保障了私有云环境下干细胞库的隐私信息安全，也为同类高密级数据的加密工作提供了全新思路。