School of Electrical Engineering, Henan University of Technology, Zhengzhou, Asia, China.
School of Information Science and Engineering, Henan University of Technology, Zhengzhou, Asia, China.
PLoS One. 2023 Oct 25;18(10):e0293418. doi: 10.1371/journal.pone.0293418. eCollection 2023.
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.
干细胞的独特的无限自我更新能力和多向分化潜能为临床治疗提供了强有力的支持。鉴于人们对干细胞储存的需求不断增长,如何确保个人隐私安全并符合严格的伦理监督要求尤为重要。为了解决传统加密算法安全性低的问题,我们提出了一种基于改进 AES 和混沌加密技术的干细胞库隐私数据双重加密保护(DEP)算法。首先,我们提出了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、转换计算,得到所构建算法中每个子系统的密钥。其次,采用两级加密实现隐私数据的 DEP 算法。第一级加密保护算法以 AES 为主要框架,在 DNA 编码的基础上添加动态编码和字节填充,并对行进行动态移位和简化的列混合。第二级加密保护算法基于我们提出的序列转换算法的结果进行随机编码、运算、扩散和解码。最后,我们提出了两个评价指标,字符变化率(NCCR)和文本统一平均变化强度(UACIT),以衡量加密算法对明文信息变化的敏感性。使用 DEP 的实验结果表明,直方图方差、信息熵、NCCR 和 UACIT 的平均值分别为 116.7883、7.6688、32.52%和 99.67%。DEP 算法具有较大的密钥空间、较高的密钥灵敏度,并能对干细胞库中的私有数据进行动态加密。本研究提供的加密方案确保了私有云环境下干细胞库私人信息的安全性,也为类似高机密性数据的加密提供了新方法。