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.
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.
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.
The advent of cryptographically relevant quantum computers poses an existential threat to current public-key cryptographic systems (RSA, ECC) widely used in digital communication protocols such as TLS, IPsec, VPNs, and secure messaging. Traditional systems face risks from "Harvest Now, Decrypt Later" attacks, compromising long-term confidentiality of sensitive data in finance, healthcare, government, and critical infrastructure. This paper proposes Quantum Shield, a comprehensive post-quantum secure framework for next-generation digital communication. It integrates NIST-standardized post-quantum algorithms (ML-KEM for key encapsulation, ML-DSA and SLH-DSA for digital signatures) with hybrid crypto-agile designs, hardware acceleration support, and role-based access controls. The system ensures quantum-resistant key establishment, authentication, and end-to-end encryption while maintaining low latency and high throughput. Experimental evaluation on simulated network traffic demonstrates acceptable performance overhead, enhanced resistance to quantum attacks, improved traceability, and secure multi-party coordination. Quantum Shield bridges the gap between classical and quantum-safe infrastructures, fostering trust and compliance in an era of quantum threats.
Purpose: The purpose of this paper is to examine the emerging threat that large-scale quantum computing poses to classical public-key cryptographic systems, particularly RSA and Elliptic Curve Cryptography (ECC), which form the backbone of contemporary digital security infrastructures. In response to this threat, the study aims to analyze post-quantum cryptography (PQC) as a viable long-term solution capable of resisting both classical and quantum adversaries. The paper further seeks to assess the urgency of PQC adoption in light of the “harvest now, decrypt later” threat model and to evaluate the practical readiness of quantum-safe cryptographic algorithms currently under consideration by the National Institute of Standards and Technology (NIST). Materials and Methods: This study employs a qualitative and analytical research methodology grounded in an extensive review of authoritative sources, including NIST’s post-quantum cryptography standardization documents, recent academic literature, industry white papers, and policy reports from organizations such as RAND Corporation and Cloudflare. The analysis systematically surveys major families of post-quantum cryptographic algorithms namely lattice-based, code-based, and hash-based schemes and evaluates them based on security assumptions, computational efficiency, implementation complexity, and standardization maturity. Findings: The analysis indicates that Lattice-based cryptographic schemes demonstrate the highest maturity and practical readiness, evidenced by their selection in NIST’s PQC process. Code- and hash-based methods provide strong security but face key size and performance challenges. The lack of scalable quantum computers does not reduce urgency, as data harvesting persists. Artificial intelligence emerges as a key enabler for accelerating PQC adoption. Unique Contribution to Theory, Practice and Policy: The paper recommends a proactive, phased post-quantum migration using hybrid cryptographic architectures. Organizations should conduct inventories, benchmarking, and pilot deployments aligned with NIST standards. AI-driven tools are advised to improve key management and reduce complexity. Continued interdisciplinary research and policy support are encouraged to ensure a secure, scalable transition to quantum-resistant security systems.
The advent of quantum computing presents a paradigm shift in modern cybersecurity, threatening the foundations of classical cryptographic systems such as RSA, ECC, and Diffie–Hellman key exchange. Quantum algorithms like Shor’s and Grover’s can efficiently break these schemes, rendering existing encryption mechanisms vulnerable and obsolete. This growing risk necessitates the development of quantum-resilient or post-quantum cryptographic (PQC) solutions that can safeguard data and computation in the era of quantum networks. Secure Multi-Party Computation (SMPC), a cornerstone of privacy-preserving computation, enables multiple entities to jointly compute a function over their private inputs without revealing them. However, its traditional security assumptions are also undermined by quantum threats. This research aims to explore and evaluate quantum-safe cryptographic protocols for integrating PQC into SMPC frameworks, thereby ensuring both confidentiality and correctness even in the presence of quantum-capable adversaries. The study focuses on lattice-based, hash-based, and code-based cryptographic primitives, analyzing their resilience, efficiency, and scalability when applied to distributed systems. A comparative framework is proposed to assess the performance and security trade-offs of different post-quantum SMPC implementations under realistic network conditions. The findings are expected to contribute to the design of a new class of cryptographic protocols capable of resisting quantum attacks, supporting the secure functioning of next-generation networks, and guiding policymakers and technologists toward practical post-quantum standardization. Ultimately, this research strengthens the bridge between theoretical cryptography and real-world cybersecurity readiness in the post-quantum era.
The emergence of quantum computing is a serious threat to traditional cryptographic algorithms, making it critical to transition to post-quantum cryptography (PQC). This work proposes a holistic conceptual and analytical framework for deploying PQC in multi-cloud environments where the complexity of different infrastructure, workloads and key management schemes pose significant security and efficiency problems. The proposed framework for crypto-agility follows a layered approach, with a cryptographic abstraction layer, a policy-based orchestration engine, a centralized hardware security module (HSM) management plane, and an ongoing monitoring module to facilitate a smooth transition from classical to hybrid and fully quantum-resistant cryptographic systems. He researches identifies and critically analyzes major challenges in deploying PQC technologies in multi-cloud environments, such as inter-cloud interoperability, computational complexity, latency, key management, and regulatory and compliance considerations. The framework tackles these challenges by incorporating hybrid cryptographic protocols that blend classic cryptographic algorithms with NIST-approved PQC algorithms, namely ML-KEM (FIPS 203) and ML-DSA (FIPS 204), to maintain backward compatibility and increase security against quantum-powered adversaries. Moreover, the framework proposes dynamic policy-driven algorithm selection to implement context-sensitive cryptographic enforcement based on sensitivity labels, security threats, and regulatory considerations. An experimental framework is proposed to assess the efficiency and scalability of PQC algorithms deployed in a multi-cloud environment, including metrics such as CPU usage, memory usage, latency and throughput with different workloads. Although this research is conceptual, it draws on previous benchmarking to discuss the securityperformance trade-offs associated with PQC. The results highlight the need for centralized trust anchors, crypto-agility and hybrid deployment models to address risks from cryptographic diversity and ensure the sustainability of security operations. This study advances the research on quantum-safe cloud security by offering a systematic, scalable and policy-oriented framework for PQC deployment. It provides practical guidance for businesses, cloud architects, and security professionals on how to safeguard against quantum vulnerabilities and ensure efficient operations in distributed systems by implementing quantum-safe cryptographic infrastructures.
This book explores the intersection of artificial intelligence (AI) and quantum computing, focusing on the urgent need to secure machine learning systems in the face of emerging quantum threats. As quantum computers advance, they expose vulnerabilities in classical cryptographic methods, potentially undermining data integrity, privacy, and trust in AI-driven applications. To address these challenges, this study introduces the concept of post-quantum AI—a framework for integrating quantum-resistant cryptographic algorithms, Anomaly detection mechanisms, and Resilient machine learning architectures. This book makes three core contributions: it motivates a quantum-era threat model for machine learning (ii) it maps a migration path to standardised post-quantum cryptography Crypto-agile architectures (iii) it presents a defence-in-depth blueprint across the data → training → inference lifecycle that integrates privacy-preserving learning Governance. This work explicitly highlights key contributions, including proposed frameworks, algorithms, and case studies. Future research directions are also outlined to guide continued exploration in this emergent field. The final candidate algorithms from the NIST PQC standardisation process (NIST, 2022–2023) further strengthen this discussion. Key themes include the foundations of quantum mechanics relevant to computation, the fundamental differences between classical and quantum computing, and the transformative potential of quantum algorithms for optimisation, pattern recognition, and predictive analytics. The book highlights case studies spanning drug discovery, finance, mobile networks, and supply chain optimisation, illustrating how quantum-enhanced AI can revolutionise industry while simultaneously raising complex security and ethical concerns. A central focus is the development and deployment of post-quantum cryptography (PQC)), such as lattice-based and hash-based algorithms, to safeguard AI models against adversarial and quantum-accelerated attacks. The discussion extends to adversarial machine learning, explainable AI (XAI), and hybrid classical–quantum systems as strategies for strengthening resilience. The ethical, legal, and regulatory dimensions of post-quantum AI are also examined, emphasising fairness, transparency, accountability, and international cooperation. By combining technical innovations with responsible governance, the book advocates for building trustworthy AI systems that remain robust in the quantum era. Future work includes post-quantum cryptography (PQC) performance benchmarking in ML pipelines Patterns for crypto-agile key management, Assurance methods for privacy-preserving Federated learning as standards, and Implementations that are mature.