MAGIQ: A Post-Quantum Multi-Agentic AI Governance System with Provable Security
- URL: http://arxiv.org/abs/2605.06933v1
- Date: Thu, 07 May 2026 20:46:07 GMT
- Title: MAGIQ: A Post-Quantum Multi-Agentic AI Governance System with Provable Security
- Abstract summary: MAGIQ is a framework for policy definition and enforcement in multi-agent AI systems.<n>We present novel, highly efficient, quantum-resistant cryptographic protocols with proven security guarantees.
- Score: 12.213634252257469
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Our computing ecosystem is being transformed by two emerging paradigms: the increased deployment of agentic AI systems and advancements in quantum computing. With respect to agentic AI systems, one of the most critical problems is creating secure governing architectures that ensure agents follow their owners' communication and interaction policies and can be held accountable for the messages they exchange with other agents. With respect to quantum computing, existing systems must be retrofitted and new cryptographic mechanisms must be designed to ensure long-term security and quantum resistance. In fact, NIST recommends that standard public-key cryptographic algorithms, including RSA, Diffie-Hellman (DH), and elliptic-curve constructions (ECC), be deprecated starting in 2030 and disallowed after 2035. In this paper, we present MAGIQ, a framework for policy definition and enforcement in multi-agent AI systems using novel, highly efficient, quantum-resistant cryptographic protocols with proven security guarantees. MAGIQ (i) allows users to define rich communication and access-control policy budgets for agent-to-agent sessions and tasks, including global budgets for one-to-many agent sessions; (ii) enforces such policies using post-quantum cryptographic primitives; (iii) supports session-based enforcement of policies for agent-to-agent and one-to-many agent sessions; and (iv) provides accountability of agents to their users through message attribution. We formally model and prove the correctness and security of the system using the Universal Composability (UC) framework. We evaluate the computation and communication overhead of our framework and compare it with the state-of-the-art agentic AI framework SAGA. MAGIQ is a first step toward post-quantum-secure solutions for agentic AI systems.
Related papers
- Foundation Protocol: A Coordination Layer for Agentic Society [78.01727114524464]
Foundation Protocol (FP) is a graph-first coordination layer for an emerging human-AI society.<n>FP unifies heterogeneous entities, including agents, tools, resources, humans, institutions, and organizations.<n>The aim is to keep autonomous agency composable while keeping accountability non-negotiable.
arXiv Detail & Related papers (2026-05-22T04:20:35Z) - Swarm Skills: A Portable, Self-Evolving Multi-Agent System Specification for Coordination Engineering [50.72456732323037]
We propose textbfSwarm Skills, a portable specification that extends the Anthropic Skills standard with multi-agent semantics.<n>Swarm Skills turns multi-agent into first-class, distributable assets that consist of roles, execution bounds, and a built-in semantic structure for self-evolution.<n>We show how Swarm Skills achieves zero-adapter cross-agent portability via progressive disclosure, enabling agent teams to self-evolve their coordination strategies without framework lock-in.
arXiv Detail & Related papers (2026-05-11T06:26:58Z) - CyberAId: AI-Driven Cybersecurity for Financial Service Providers [0.7279162155456086]
We present CyberAId, a model-agnostic, on-premise-deployable platform in which a Main Agent coordination layer, a Reporting capability, and specialist subagents operate within a shared runtime under bounded human-in-the-loop autonomy.
arXiv Detail & Related papers (2026-05-03T14:15:11Z) - Architecting Secure AI Agents: Perspectives on System-Level Defenses Against Indirect Prompt Injection Attacks [46.32011684548212]
AI agents are vulnerable to indirect prompt injection, in which malicious instructions embedded in untrusted data can trigger dangerous agent actions.<n>This position paper discusses our vision for system-level defenses against indirect prompt injection attacks.
arXiv Detail & Related papers (2026-03-31T17:15:46Z) - Quantum-Secure-By-Construction (QSC): A Paradigm Shift For Post-Quantum Agentic Intelligence [0.0]
Quantum secure by construction, or QSC, is a design paradigm that treats quantum secure communication as a core architectural property of agentic AI systems.<n>We realize QSC through a runtime adaptive security model that combines post quantum cryptography, quantum random number generation, and quantum key distribution.<n>We show that QSC can reduce the operational complexity and cost of introducing quantum security into deployed agentic AI systems.
arXiv Detail & Related papers (2026-03-12T17:38:02Z) - Just Ask: Curious Code Agents Reveal System Prompts in Frontier LLMs [65.6660735371212]
We present textbftextscJustAsk, a framework that autonomously discovers effective extraction strategies through interaction alone.<n>It formulates extraction as an online exploration problem, using Upper Confidence Bound--based strategy selection and a hierarchical skill space spanning atomic probes and high-level orchestration.<n>Our results expose system prompts as a critical yet largely unprotected attack surface in modern agent systems.
arXiv Detail & Related papers (2026-01-29T03:53:25Z) - Towards 6G Native-AI Edge Networks: A Semantic-Aware and Agentic Intelligence Paradigm [85.7583231789615]
6G positions intelligence as a native network capability, transforming the design of radio access networks (RANs)<n>Within this vision, Semantic-native communication and agentic intelligence are expected to play central roles.<n>Agentic intelligence endows distributed RAN entities with goal-driven autonomy, reasoning, planning, and multi-agent collaboration.
arXiv Detail & Related papers (2025-12-04T03:09:33Z) - The Aegis Protocol: A Foundational Security Framework for Autonomous AI Agents [0.0]
The proliferation of autonomous AI agents marks a paradigm shift toward complex, emergent multi-agent systems.<n>This paper introduces the Aegis Protocol, a layered security framework designed to provide strong security guarantees for open agentic ecosystems.
arXiv Detail & Related papers (2025-08-22T06:18:57Z) - TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems [8.683314804719506]
This review presents a structured analysis of Trust, Risk, and Security Management (TRiSM) in the context of Agentic Multi-Agent Systems (AMAS)<n>We begin by examining the conceptual foundations of Agentic AI and highlight its architectural distinctions from traditional AI agents.<n>We then adapt and extend the AI TRiSM framework for Agentic AI, structured around key pillars: textit Explainability, ModelOps, Security, Privacy and textittheir lifecycle governance<n>A risk taxonomy is proposed to capture the unique threats and vulnerabilities of Agentic AI, ranging from coordination failures to
arXiv Detail & Related papers (2025-06-04T16:26:11Z) - LLM Agents Should Employ Security Principles [60.03651084139836]
This paper argues that the well-established design principles in information security should be employed when deploying Large Language Model (LLM) agents at scale.<n>We introduce AgentSandbox, a conceptual framework embedding these security principles to provide safeguards throughout an agent's life-cycle.
arXiv Detail & Related papers (2025-05-29T21:39:08Z) - A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control [7.228060525494563]
This paper posits the imperative for a novel Agentic AI IAM framework.<n>We propose a comprehensive framework built upon rich, verifiable Agent Identities (IDs)<n>We also explore how Zero-Knowledge Proofs (ZKPs) enable privacy-preserving attribute disclosure and verifiable policy compliance.
arXiv Detail & Related papers (2025-05-25T20:21:55Z) - Agent-as-a-Judge: Evaluate Agents with Agents [61.33974108405561]
We introduce the Agent-as-a-Judge framework, wherein agentic systems are used to evaluate agentic systems.
This is an organic extension of the LLM-as-a-Judge framework, incorporating agentic features that enable intermediate feedback for the entire task-solving process.
We present DevAI, a new benchmark of 55 realistic automated AI development tasks.
arXiv Detail & Related papers (2024-10-14T17:57:02Z) - Counterfactual Multi-Agent Policy Gradients [47.45255170608965]
We propose a new multi-agent actor-critic method called counterfactual multi-agent (COMA) policy gradients.<n>COMA uses a centralised critic to estimate the Q-function and decentralised actors to optimise the agents' policies.<n>We evaluate COMA in the testbed of StarCraft unit micromanagement, using a decentralised variant with significant partial observability.
arXiv Detail & Related papers (2017-05-24T18:52:17Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.