首页|基于Merkle哈希树的电力扰动数据安全去重方法

基于Merkle哈希树的电力扰动数据安全去重方法

Secure Deduplication Method for Power Disturbance Data Based Merkle Hash Tree

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针对当前去重方法存在伪基和伪偏移量问题,导致去重效果不佳,提出了基于Merkle哈希树的电力扰动数据安全去重方法.使用收敛加密方法,有效解决数据加密和去重矛盾,应用Merkle哈希树得到电力扰动数据块指纹,以此标记待去重电力扰动数据.利用POW协议证明拥有权检测重复数据块.使用扰动状态似然代替对数似然,避免电力异常扰动状态在去重标识过程中重复,实现安全去重.由实验结果可知,该方法最大基提取为3000 B、最大偏移量为6000 B,均未超过实验设定阈值,说明所提方法去重效果较好.
In view of the problems of pseudo-base and pseudo-offset in the current de-weight method,the effect of de-weight is not good.This paper presents a safe method for removing power disturbance data based on Merkle hash tree.Con-vergence encryption method is used to effectively solve the contradiction between data encryption and deduplication.Merkle hash tree is used to obtain power disturbance data block fingerprint,which marks the power disturbance data to be de-dupli-cated.Duplicate data blocks are detected using POW protocol to prove ownership.The disturbance state likelihood is used instead of logarithmic likelihood to avoid repeating abnormal disturbance state in the process of deregistration and achieve safe deregistration.The experimental results show that the maximum base extraction of the method is 3000 B and the maxi-mum offset is 6000 B,both of which do not exceed the threshold set by the experiment,indicating that the proposed method has a good effect of weight removal.

Merkle Hash treepower disturbancedata security deduplicationprobability error

李世明、卢建刚、余志文、郭文鑫、汤健东

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广东电网有限责任公司电力调度控制中心,广东广州 510000

国电南瑞南京控制系统有限公司,江苏南京 210000

Merkle哈希树 电力扰动 数据安全去重 概率误差

2024

计算技术与自动化
湖南大学

计算技术与自动化

CSTPCD
影响因子:0.295
ISSN:1003-6199
年,卷(期):2024.43(3)