使用分散方法保护医疗保健数据

Dodla Navya Shree, Dodda Venkata Lohitha Krishna, Rizwan Patan
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引用次数: 1

摘要

据世界卫生组织称,脑中风似乎是第二大常见原因,占所有死亡人数的11%左右。医疗保健行业对数据安全和隐私的需求很大。数据现在以集中的方式保存在现有的系统中,所有数据都存储在一个区域。在这样的系统中,入侵者或第三方访问和更改数据的可能性很大。在医疗保健中,由于数据是最关键的因素,因此如果入侵者对数据进行了任何微小的更改,都可能导致提供错误的结果。在这个拟议的系统中,使用IPFS(星际文件系统)协议和区块链以分散的方式保护数据。使用此策略可以降低数据故障和中断的风险,同时提高安全性、性能和隐私性。使用哈希值从IPFS网络中收集所需的数据,并使用ANN(人工神经网络)算法进行训练,得到最终模型。
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Securing Healthcare Data using Decentralized Approach
According to WHO, brain stroke seems to be the second most common cause overall, accounting for about eleven percent of all mortality. Data security and privacy are in great demand in the healthcare industry. Data is now kept in a centralized manner in present systems, with all data being stored in a single area. In such systems, there is a high possibility for an intruder or third party to access and change the data. In Healthcare, as the data is the most crucial factor, so if there are any small changes made by the intruder in the data, it may lead to provide false outcome. In this proposed system, the data are secured in a decentralized approach using IPFS (InterPlanetary File System) protocol and Block chain. The risk of data failures and outages can be reduced while improving security, performance, and privacy using this strategy. The required data will be collected from the IPFS network by using the hash value and it will be trained with the ANN (Artificial Neural Network) algorithm to get the final model.
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