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Work item:
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QSTR-AI4CDD
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Subject/title:
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AI-enabled behavioural detection framework for counterfeit ICT devices in operational networks
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Status:
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Under study
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Approval process:
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Agreement
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Type of work item:
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Technical report
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Version:
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New
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Equivalent number:
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-
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Timing:
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2027-Q1 (Medium priority)
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Liaison:
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ITU-T SG2, ITU-T SG13, FG-AINN, ITU-T SG15, ITU-T SG17, ITU-T SG20, ITU-D SG2 Q4/2
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Supporting members:
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Ghana, Botswana, C-DOT (India)
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Summary:
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This Technical Report analyses the potential application of artificial intelligence (AI) techniques to support the detection of counterfeit or non-compliant telecommunication/ICT devices operating within live telecommunication networks.
Existing mitigation approaches for combating counterfeit devices mainly focus on preventive measures prior to deployment, including certification mechanisms, supply-chain verification, and equipment identification procedures. However, once devices are deployed in operational networks, counterfeit or tampered equipment may evade traditional verification mechanisms.
This report investigates AI-enabled behavioural analysis as a complementary approach to post-deployment detection. Behavioural indicators derived from network traffic patterns, signalling behaviour, protocol interactions, and network performance metrics may help identify anomalies associated with counterfeit devices.
The report presents a conceptual framework and reference architecture for behavioural detection mechanisms and outlines potential application domains for future study.
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Comment:
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-
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Reference(s):
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Historic references:
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Contact(s):
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First registration in the WP:
2026-03-20 15:19:19
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Last update:
2026-03-20 15:24:50
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