Russian authorities are working on initiatives to automatically identify and restrict traffic obfuscation services using artificial intelligence. The goal is to analyze parameters of approximately 70% of target systems, aiming for a blocking efficiency of up to 95%. Simultaneously, the capacity of the traffic filtering infrastructure is planned to expand 2.5 times to 954 Tbps by 2030.
Technical Mechanisms and Implementation Challenges
The analytical algorithms are expected to be deployed directly onto provider-level filtering equipment. Rather than decrypting payload contents, the system will evaluate behavior patterns such as data transfer volumes, session lengths, packet timing intervals, and related IP addresses. This methodology enables the identification of anonymizer infrastructure through indirect indicators.
However, practical implementation faces challenges regarding false positives. Currently, error rates in filtering equipment reach 5-6%, and early rollout of artificial intelligence systems could disrupt legitimate business traffic. Furthermore, establishing massive telemetry storage and specialized compute clusters is necessary for model training.
Adoption of National Encryption Standards
In addition to network-level restrictions, plans are being developed to require support for the domestic Kuznechik encryption algorithm in 5G mobile devices. As this standard is not part of global hardware specifications, major technology manufacturers may need to produce tailored hardware revisions for the local market by 2032.
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