Blockchain and credibility function based chain storage method of electronic encrypted information

Ting ZHOU

doi:10.11959/j.issn.1000-0801.2023147

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Blockchain and credibility function based chain storage method of electronic encrypted information

Research and Development | 更新时间：2024-06-05

- Blockchain and credibility function based chain storage method of electronic encrypted information
- Telecommunications Science Vol. 39, Issue 7, Pages: 116-123(2023)
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- DOI：10.11959/j.issn.1000-0801.2023147
  CLC： TP309
- Published Online：2023-07，
  
  Published：20 July 2023
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Ting ZHOU. Blockchain and credibility function based chain storage method of electronic encrypted information[J]. Telecommunications science, 2023, 39(7): 116-123.
DOI：

Ting ZHOU. Blockchain and credibility function based chain storage method of electronic encrypted information[J]. Telecommunications science, 2023, 39(7): 116-123. DOI： 10.11959/j.issn.1000-0801.2023147.

摘要

为优化加密信息在区块链的存储空间占比，提高上链存储速度，提出了基于区块链与可信度函数设计电子加密信息上链存储方法。建立基于区块链和可信度函数的信息加密分类模型，获取溯源凭证判定函数，对电子信息进行代理重加密；计算集群存储空间容量，使用加密密文直接匹配访问结构树；区分主体可信度与客体可信度，基于可信度函数分类电子加密信息，设计电子加密信息上链存储方法。实验结果表明，应用所提方法后，当文件数量在1 000～10 000个时，数据存储速度最快，存储空间占比以及存储速度上均有较大优化。

Abstract

To optimize the proportion of encrypted information storage space in the blockchain and improve the speed of online storage

a design method for electronic encrypted information online storage based on blockchain and credibility function was proposed.An information encryption classification model based on blockchain and credibility function was established

and a traceability voucher judgment function was obtained.Proxy re-encryption was performed on electronic information.The storage capacity of the cluster was calculated

and encrypted ciphertext was used to directly match the access structure tree.Subject credibility and object credibility were distinguished

electronic encrypted information was classified based on the credibility function

and an electronic encrypted information uplink storage method was designed.The experimental results show that after applying the proposed method

when the number of files is between 1 000 and 10 000

the data storage speed is the fastest

and the storage space proportion and storage speed are greatly optimized.

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references

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