mlsanityData to 14 Oct 2026

Quantum-Secure-By-Construction (QSC): A Paradigm Shift For Post-Quantum Agentic Intelligence

arXiv 2603.15668 ↗First posted 12 Mar 2026cs.AI cs.CR quant-phcited by 0

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Abstract (arXiv)

As agentic artificial intelligence systems scale across globally distributed and long lived infrastructures, secure and policy compliant communication becomes a fundamental systems challenge. This challenge grows more serious in the quantum era, where the cryptographic assumptions built into today's AI deployments may not remain valid over their operational lifetime. Here, we introduce quantum secure by construction, or QSC, as a design paradigm that treats quantum secure communication as a core architectural property of agentic AI systems rather than an upgrade added later. We realize QSC through a runtime adaptive security model that combines post quantum cryptography, quantum random number generation, and quantum key distribution to secure interactions among autonomous agents operating across heterogeneous cloud, edge, and inter organizational environments. The approach is cryptographically pluggable and guided by policy, allowing the system to adjust its security posture according to infrastructure availability, regulatory constraints, and performance needs. QSC contributes a governance aware orchestration layer that selects and combines link specific cryptographic protections across the full agent lifecycle, including session bootstrap, inter agent coordination, tool invocation, and memory access. Through system level analysis and empirical evaluation, we examine the trade offs between classical and quantum secure mechanisms and show that QSC can reduce the operational complexity and cost of introducing quantum security into deployed agentic AI systems. These results position QSC as a foundational paradigm for post quantum agentic intelligence and establish a principled pathway for designing globally interoperable, resilient, and future ready intelligent systems.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 67 references that are in the map. First posted on arXiv 12 Mar 2026.

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12 of 67 references.

References · 12

  1. 2023Sparks of Artificial General Intelligence: Early experiments with GPT-4cited by 2,592
  2. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
  3. 2025Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directionscited by 265
  4. 2025AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challengescited by 169
  5. 2025Agentic AI Frameworks: Architectures, Protocols, and Design Challengescited by 16
  6. 2023Quantum neural networks form Gaussian processescited by 12
  7. 2017An All-Pair Quantum SVM Approach for Big Data Multiclass Classificationcited by 6
  8. 2025A Comparative Study of Classical and Post-Quantum Cryptographic Algorithms in the Era of Quantum Computingcited by 2
  9. 2023Quantum Cryptography for Enhanced Network Security: A Comprehensive Survey of Research, Developments, and Future Directionscited by 1
  10. 2024Strategic Roadmap for Quantum- Resistant Security: A Framework for Preparing Industries for the Quantum Threatcited by 1
  11. 2025Quantum-enabled framework for the Advanced Encryption Standard in the post-quantum eracited by 1
  12. 2025Performance Analysis and Industry Deployment of Post-Quantum Cryptography Algorithmscited by 1

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  6. 2025SAGA: A Security Architecture for Governing AI Agentic Systems
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  8. 2026AI-Assisted Design of a Post-Quantum Cryptographic Accelerator: A Deployed-Silicon Case Study ↗