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ITU-T X.1753 (12/2025)

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Guidelines for data security using machine learning in big data infrastructure
In big data infrastructure, there are many security threats in the process of data collection, storage, processing, and management. How to dynamically and intelligently monitor, analyse, and respond to data security threats is a problem to be solved in big data infrastructure. Machine learning has the capabilities of automatic learning and pattern recognition, which can discover potential security threats and abnormal behaviours from a large amount of data so that proactive defensive measures can be taken. Using machine learning to enhance data security has gradually become a necessary technology for big data infrastructure.
Recommendation ITU-T X.1753 analyses data security threats in big data infrastructure and scenarios where machine learning can be applied to data security protection in big data infrastructure and provides guidelines for using machine learning to protect data security of big data infrastructure.
Citation: https://handle.itu.int/11.1002/1000/16485
Series title: X series: Data networks, open system communications and security
  X.1750-X.1799: Data security
  X.1750-X.1759: Big Data Security
Approval date: 2025-12-11
Provisional name:X.gdsml
Approval process:TAP
Status: In force
Maintenance responsibility: ITU-T Study Group 17
Further details: Patent statement(s)
Development history
[16 related work items in progress]