|
Work item:
|
XSTR.AIS-IMT2030
|
|
Subject/title:
|
Benefits and challenges of AI-enabled security for IMT-2030 networks
|
|
Status:
|
|
|
Approval process:
|
Agreement
|
|
Type of work item:
|
Technical report
|
|
Version:
|
New
|
|
Equivalent number:
|
-
|
|
Timing:
|
-
|
|
Liaison:
|
ITU-T SG13, 3GPP SA WG3, 3GPP SA WG2
|
|
Supporting members:
|
China Mobile, BUPT, ZTE, CAICT, China Telecom
|
|
Summary:
|
Existing telecom network analysis and decision-making suffer from problems including data fragmentation, poor real-time responsiveness, insufficient prediction capability, heavy manual dependence, static and rigid policies, poor cross-domain collaboration, and lack of intelligent closed-loop capabilities. These issues make it difficult to meet the high-security, differentiated, and highly dynamic network requirements of IMT-2030.Artificial intelligence can effectively compensate for the shortcomings of traditional network security analysis and decision-making through global data convergence, real-time situational awareness, intelligent feature mining, predictive analysis, adaptive decision-making, and closed-loop autonomy.Capabilities supported by the IMT-2030 network, such as AI capability, digital twinning, and data services, make it possible to further enhance the intelligence of security capabilities. However, while AI enablement brings the potential for security optimization, it also poses challenges in meeting the functional and performance requirements imposed by the characteristics of telecommunications networks.
This technical report identifies use cases for AI-enabled security in IMT-2030, and analyzes existing challenges, potential application scenarios, candidate requirements and principles, technology maturity investigations, and illustrative solution examples. It provides guidance on integrating AI to enhance security in IMT-2030, and instructs how AI-enabled security can be integrated into the IMT-2030 architecture design and its relationship with other components. This report is intended to help operators assess whether and how to adopt AI-enabled security, assist equipment vendors and security service providers in supporting its implementation, and enable AI service providers to understand the requirements of AI applications in the telecommunications industry, thereby facilitating the extension of AI capabilities into the telecom sector.
|
|
Comment:
|
-
|
|
Reference(s):
|
|
|
Historic references:
|
|
Contact(s):
|
|
| ITU-T A.5 justification(s): |
|
|
|
|
First registration in the WP:
2026-04-02 10:41:34
|
|
Last update:
2026-04-02 16:20:05
|
|
