边缘人工智能和区块链用于隐私关键和数据敏感应用

Anum Nawaz, Tuan Anh Nguyen Gia, J. P. Queralta, Tomi Westerlund
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引用次数: 29

摘要

边缘计算和雾计算范例使系统响应更快、更智能,而无需依赖云服务器进行数据处理和存储。这减少了网络负载和延迟。尽管如此,网络体系结构中新层的增加增加了安全漏洞的数量。在隐私关键型系统中,新漏洞的出现更为重要。为了解决这个问题,我们提出并实现了一个基于以太坊区块链的架构,该架构具有边缘人工智能,可以分析网络边缘的数据,并跟踪访问分析结果的各方,这些分析结果存储在分布式数据库中。
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Edge AI and Blockchain for Privacy-Critical and Data-Sensitive Applications
The edge and fog computing paradigms enable more responsive and smarter systems without relying on cloud servers for data processing and storage. This reduces network load as well as latency. Nonetheless, the addition of new layers in the network architecture increases the number of security vulnerabilities. In privacy-critical systems, the appearance of new vulnerabilities is more significant. To cope with this issue, we propose and implement an Ethereum Blockchain based architecture with edge artificial intelligence to analyze data at the edge of the network and keep track of the parties that access the results of the analysis, which are stored in distributed databases.
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