protocol design

This study addresses the severe fragmentation of large language model (LLM) communication protocols in multi-agent systems, which significantly hinders interoperability. The work proposes the first structured taxonomy specifically tailored to LLM agent communication protocols, developed through an empirical-conceptual bidirectional iterative approach. By systematically analyzing nine prominent open-source protocols, the authors derive a five-dimensional classification framework encompassing communication parties, payload structure, interaction state, discovery mechanisms, and pattern flexibility. The analysis identifies recurring architectural patterns—including hybrid payloads, persistent conversation states, and runtime protocol negotiation—revealing commonalities and evolutionary trends across existing protocols. The study further forecasts a trajectory toward federated, layered protocol stacks and highlights critical research gaps, particularly in privacy preservation and policy enforcement, thereby offering theoretical guidance for future protocol design and selection.

This work addresses the semantic gap between informal protocol specifications—such as IETF RFCs—and formal specifications. It introduces a cognitive discrepancy analysis framework that identifies fundamental limitations in RFCs, including semantic ambiguity, unstated assumptions, and logical inconsistency. Methodologically, the approach integrates formal specification languages (e.g., TLA⁺), state-machine modeling, and protocol conformance testing to perform semantic parsing and cross-version consistency checking on real-world RFC texts and reference implementations. A key contribution is the establishment of a collaborative paradigm bridging industry practitioners and formal methods researchers, facilitating the evolution of RFCs into verifiable, executable formal specifications. Empirical evaluation demonstrates that this methodology significantly improves defect detection rates, interoperability assurance, and depth of security verification. The proposed framework provides a reusable, scalable foundation for formalizing next-generation Internet protocol standards.

This study addresses the realizability of global distributed protocols under asynchronous network architectures—specifically, whether local implementations can satisfy global specifications. To this end, the work introduces a network-parameterized coherence condition, combined with operational axioms that characterize message buffering behavior, enabling a unified formal model of five prominent asynchronous network paradigms. Leveraging symbolic algorithms and formal verification techniques, the paper establishes—for the first time—a systematic relationship between network architecture parameters and protocol realizability, and derives optimal complexity bounds. The accompanying tool, Sprout(A), is the first realizability verifier supporting multiple network architectures, achieving both high performance and modularity without sacrificing generality.

Transport-layer protocol development is hindered by environmental heterogeneity and the absence of high-level, target-agnostic programming abstractions, impeding automated analysis, formal verification, and programmable transport research. To address this, we propose TINF—the first event-driven, state-aware, high-level programming abstraction specifically designed for transport protocols—achieving full decoupling between protocol logic and execution targets. TINF employs a C-like restricted syntax to express protocol behavior and introduces a target-agnostic instruction set supporting core operations including data reassembly, packet generation, scheduling, and timer management. It features dual backends: DPDK and Linux XDP. Experimental evaluation demonstrates that TINF significantly improves development efficiency, ensures cross-platform semantic consistency, and establishes a unified foundation for formal modeling and automated verification of transport protocols.

Ensuring functional correctness and performance resilience of network protocols under component failures and adversarial attacks remains a significant challenge. Method: This paper proposes a synergistic analysis framework integrating formal verification with attack synthesis. It models protocol behavior using a formal specification language and employs logical predicates, trace analysis, and model checking to achieve closed-loop verification—simultaneously establishing correctness guarantees and automatically generating realistic attack scenarios. Contribution/Results: Diverging from conventional unidirectional verification, our approach innovatively embeds attack-path generation directly into the verification workflow, enabling reproducible and interpretable failure attribution. Experimental evaluation across multiple mainstream network protocols demonstrates substantial improvements in vulnerability detection rates and attack-surface characterization accuracy. The results validate the feasibility and practicality of formal methods for deep, security-critical analysis of complex network protocols.

Detecting and reproducing boundary-case vulnerabilities—especially those arising from state machine logic flaws in network protocols—remains challenging for conventional fuzzing due to inadequate coverage and poor reproducibility. Method: This paper proposes the first closed-loop approach integrating formal protocol specification inference, lightweight symbolic execution, and controllable vulnerability trace generation. It leverages SMT-driven state modeling, automatic synthesis of protocol interaction constraints, and automated proof-of-concept (PoC) generation to achieve end-to-end automation from vulnerability discovery to precise reproduction. Contribution/Results: Evaluated on 12 mainstream protocol stacks, the method discovers 17 previously unknown vulnerabilities—including 6 assigned CVEs—with an average reproduction time under 8 seconds and a false positive rate below 3%. It significantly improves accuracy, interpretability, and reproducibility in deep protocol vulnerability detection.

Current agent communication protocols generally lack mechanisms for semantic alignment, clarification, and verification, shifting semantic responsibility onto prompts or application logic and thereby causing poor interoperability and high maintenance costs. This work proposes, for the first time, a human-inspired three-layer communication framework—comprising communication, syntactic, and semantic layers—and systematically analyzes 18 mainstream protocols to expose their structural deficiencies in semantic coordination. Through layered modeling, technical debt identification, and scenario mapping, the study not only derives a practical protocol selection guide but also advances agent communication beyond mere message passing toward a new paradigm of shared understanding, laying the foundation for building semantically robust, secure, and interoperable agent ecosystems.

Existing transport-layer hardware struggles to flexibly support the evolution of new protocols due to rigid protocol logic or reliance on protocol-specific assumptions. This work proposes PITA, a novel architecture that reconfigures core components—such as scheduling, packet generation, and data reassembly—through a unified event–state–instruction abstraction model, enabling a protocol-agnostic and line-rate programmable transport-layer datapath. By eliminating protocol-specific assumptions, PITA efficiently supports semantically diverse protocols, including TCP and RoCE, on a single FPGA (Alveo U250) while fully preserving their end-to-end behavioral differences. Experimental results demonstrate that the system meets timing constraints at 250 MHz with low hardware overhead and excellent performance.

Existing agent interoperability protocols primarily focus on task coordination and lack support for governance-constrained collective decision-making in multi-agent communities. Drawing on organizational theory and corporate governance standards, this work proposes a six-dimensional governance framework encompassing membership management, deliberation, voting, dissent reservation, human escalation, and audit replay. The study systematically evaluates five prominent protocols—MCP, A2A, ACP, and others—and reveals, for the first time, that the core deficiency lies not in insufficient protocol-level features but in the absence of a dedicated architectural layer for governance. It further distinguishes between scalability gaps and structural gaps. The analysis demonstrates that current protocols universally lack voting and dissent reservation mechanisms, provide only partial support for deliberation, and offer no complete set of governance primitives.

Existing agent programming models struggle to coordinate internal decision-making with external interaction behaviors and lack effective abstractions for protocol adherence. This work proposes Kiko, a protocol-based agent programming model that introduces a decider abstraction, enabling agents to select actions and generate protocol-compliant messages exclusively from the set of legally permissible moves, thereby strictly adhering to interaction protocols in decentralized environments. Kiko fully encapsulates low-level communication details, supports flexible decision-making strategies, and integrates formal operational semantics to guarantee correct execution of arbitrary protocols. By doing so, it allows developers to focus on business logic while ensuring correctness and reliability in protocol enforcement within multi-agent systems.