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Take "Data Intelligence Knowledge Map" Privacy Computing Knowledge System
The concept, development history, technical principles, main algorithms, application scenarios, industrial development, legal compliance, etc. of privacy computing are discussed, and relevant issues and trends are analyzed. Privacy computing is a cross-fusion technology covering many disciplines. At present, the mainstream privacy computing technology is mainly divided into three directions: the first category is cryptography-based privacy computing technology represented by multi-party secure computing; the second category is federated learning The third category is the trusted hardware-based privacy computing technology represented by the trusted execution environment. Different technologies are often used in combination to complete the calculation and analysis tasks of data while ensuring the security and privacy of the original data. The following figure explains the privacy computing knowledge system in detail.
"Data Intelligence Knowledge Map"
The data intelligence knowledge map, compiled and released by the datafun community, includes four major areas: data collection and governance, data architecture, data capabilities, and data applications. It includes not only relatively traditional technical modules such as data collection, data governance, and data warehouse, but also cloud computing. Native, causal inference, pre-training and other cutting-edge technology modules, this official account will sort out and release them one by one.
Source: Organized from datafun data intelligent knowledge map
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