Driven by the rapid advancement of Agentic AI and autonomous agents, next-generation intelligent
networks are undergoing a fundamental transformation from connecting people to connecting intelligence. As network architectures and service paradigms continue to evolve, future networks are expected to become increasingly decentralized, intelligent, and heterogeneous. While these developments unlock unprecedented capabilities, they also introduce new challenges related to security, trustworthiness, and governance. Existing Zero Trust architectures have played a significant role in conventional networks; however, their reliance on static policies, identity-centric access control, and centralized trust evaluation mechanisms may be insufficient to address the emerging characteristics of agentic environments, including autonomous decision-making, distributed collaboration, heterogeneous cross-domain interactions, and complex task execution.<\/p>\n\n\n\n
Multi-party trust<\/strong> addresses the limitations of centralized trust authorities by promoting multi-party Driven by the rapid advancement of Agentic AI and autonomous agents, next-generation intelligentnetworks are undergoing a fundamental transformation from connecting people to connecting intelligence. As network architectures and service paradigms continue to evolve, future networks are expected to become increasingly decentralized, intelligent, and heterogeneous. While these developments unlock unprecedented capabilities, they also introduce new challenges […]<\/p>\n","protected":false},"author":64,"featured_media":0,"template":"","meta":{"image":"https:\/\/www.gsma.com\/about-us\/regions\/greater-china\/wp-content\/uploads\/2026\/09\/EN.png","json":{"gsma_resources_type":"Other","gsma_resources_thumb":"[12343]","gsma_resources_file":"null","gsma_resources_multi":null,"gsma_resources_wgr":null,"gsma_resources_video":"","gsma_resources_image":"[12343]","gsma_resources_url":"","gsma_resources_date":"","gsma_resources_button":""}},"tags":[],"resource_categories":[],"algolia_discover_type":[],"yoast_head":"\n
To address these challenges, this white paper proposes a new trust framework for future intelligent
networks: the MAIC-Trust Framework (hereinafter referred to as M-Trust).<\/strong> The framework extends trust beyond traditional identity-based security and introduces three complementary dimensions for building a trustworthy agentic network environment:<\/p>\n\n\n\n
participation, decentralized decision-making, and diversified trust models. It provides a foundation for
collaborative trust governance through mechanisms such as endorsement-based and consensus-based trust evaluation.
Agentic Intent-aware trust<\/strong> focuses on the trustworthiness of intelligent agents themselves. It extends traditional identity verification mechanisms toward an integrated model of Identity Verification and Intent-aware Authorization<\/strong>, enabling adaptive authorization decisions that consider task objectives, execution context, resource requests, and risk conditions. This approach aims to strengthen security while avoiding unnecessary operational overhead.
Cross-domain trust<\/strong> addresses heterogeneous networking environments and cross-domain interactions by introducing cross-domain trust propagation mechanisms and support for heterogeneous trust anchors. This enables trust to be established, maintained, and interoperated across different networks and administrative domains while preserving consistency and availability.<\/p>\n\n\n\n
The framework further introduces a layered architecture consisting of a Trust Collection and Evaluation Layer, a Policy Decision Layer, and a Policy Enforcement Layer. Together, these layers establish an end-to-end trust lifecycle of sensing, decision-making, and enforcement. In addition, the white paper discusses enabling technologies associated with Multi-party trust, Agentic Intent-aware trust, and Cross-domain trust, and clarifies the positioning of M-Trust as an evolution of, rather than a replacement for, Zero Trust. The framework serves as a reference architecture for future intelligent communication networks and provides a foundation for further research and industry exploration.<\/p>\n","protected":false},"excerpt":{"rendered":"