The rapid progress of quantum computing poses substantial risks to classical cryptographic mechanisms widely deployed in Big Data processing systems, whose distributed architectures, high computational intensity, and exposure to diverse attack vectors impose stringent requirements on long-term security and reliability. Accordingly, this study aims to develop a risk-oriented framework for assessing post-quantum cryptographic (PQC) algorithms in large-scale data environments. The proposed methodology integrates cryptographic reliability and computational efficiency within a unified multi-criteria decision-making model, incorporating formalised threat modelling, probabilistic analysis of resistance to classical and quantum attacks, robustness evaluation under high computational loads, and quantitative performance metrics, including latency, throughput, resource consumption, and scalability in distributed infrastructures. Based on this framework, a comparative analysis of representative classes of PQC algorithms is conducted in typical Big Data processing scenarios. The results indicate that different PQC families exhibit distinct security–performance trade-offs and that no single algorithm is universally optimal across all operational conditions. The study concludes that a risk-oriented, multi-criteria selection of post-quantum cryptographic mechanisms enhances the overall resilience and operational efficiency of secure Big Data systems, providing a practical foundation for their design, modernisation, and cybersecurity governance in the post-quantum era.
The rapid progress of quantum computing poses substantial risks to classical cryptographic mechanisms widely deployed in Big Data processing systems, whose distributed architectures, high computational intensity, and exposure to diverse attack vectors impose stringent requirements on long-term security and reliability. Accordingly, this study aims to develop a risk-oriented framework for assessing post-quantum cryptographic (PQC) algorithms in large-scale data environments. The proposed methodology integrates cryptographic reliability and computational efficiency within a unified multi-criteria decision-making model, incorporating formalised threat modelling, probabilistic analysis of resistance to classical and quantum attacks, robustness evaluation under high computational loads, and quantitative performance metrics, including latency, throughput, resource consumption, and scalability in distributed infrastructures. Based on this framework, a comparative analysis of representative classes of PQC algorithms is conducted in typical Big Data processing scenarios. The results indicate that different PQC families exhibit distinct security–performance trade-offs and that no single algorithm is universally optimal across all operational conditions. The study concludes that a risk-oriented, multi-criteria selection of post-quantum cryptographic mechanisms enhances the overall resilience and operational efficiency of secure Big Data systems, providing a practical foundation for their design, modernisation, and cybersecurity governance in the post-quantum era.
The rapid progress of quantum computing poses substantial risks to classical cryptographic mechanisms widely deployed in Big Data processing systems, whose distributed architectures, high computational intensity, and exposure to diverse attack vectors impose stringent requirements on long-term security and reliability. Accordingly, this study aims to develop a risk-oriented framework for assessing post-quantum cryptographic (PQC) algorithms in large-scale data environments. The proposed methodology integrates cryptographic reliability and computational efficiency within a unified multi-criteria decision-making model, incorporating formalised threat modelling, probabilistic analysis of resistance to classical and quantum attacks, robustness evaluation under high computational loads, and quantitative performance metrics, including latency, throughput, resource consumption, and scalability in distributed infrastructures. Based on this framework, a comparative analysis of representative classes of PQC algorithms is conducted in typical Big Data processing scenarios. The results indicate that different PQC families exhibit distinct security–performance trade-offs and that no single algorithm is universally optimal across all operational conditions. The study concludes that a risk-oriented, multi-criteria selection of post-quantum cryptographic mechanisms enhances the overall resilience and operational efficiency of secure Big Data systems, providing a practical foundation for their design, modernisation, and cybersecurity governance in the post-quantum era.
Purpose: This study presents a comprehensive post-quantum cryptographic framework designed to secure Critical Digital Public Infrastructure (DPI) against emerging quantum computing threats. Methodology: As traditional cryptographic methods become increasingly vulnerable, the proposed framework integrates post-quantum algorithms, hybrid cryptographic models, and a multi-layered architecture to ensure long-term data protection. The system is evaluated using key performance metrics such as latency, throughput, energy consumption, overhead, key size, and security strength. Additionally, an algorithm selection strategy is implemented to identify optimal cryptographic techniques. Findings: Simulation results demonstrate that classical models offer better efficiency, while post-quantum approaches provide stronger security at the cost of higher resource usage. The hybrid model effectively balances these trade-offs, delivering improved security with moderate performance impact. Unique Contribution to Theory, Policy and Practice: Overall, the framework provides a scalable, adaptable, and future-ready solution for protecting critical infrastructure in a rapidly evolving digital and quantum landscape.
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.
The rapid advancement of quantum computing introduces unprecedented security threats to modern cloud and edge computing infrastructures. Classical public-key cryptographic algorithms such as RSA, Diffie–Hellman, and Elliptic Curve Cryptography (ECC) are fundamentally vulnerable to quantum attacks enabled by Shor’s algorithm. As a result, the confidentiality, integrity, and authenticity of data stored and processed in distributed systems are at serious risk.Post-quantum cryptography (PQC) aims to develop cryptographic algorithms that are resistant to both classical and quantum adversaries. This paper presents a comprehensive quantum-resilient cryptographic framework designed specifically for post-quantum cloud and edge computing environments. The framework integrates post-quantum cryptographic primitives, hybrid cryptographic approaches, crypto-agile architectures, and secure key management mechanisms. The proposed framework addresses performance constraints, scalability requirements, and deployment challenges in heterogeneous environments. A detailed discussion of security threats, architectural components, performance considerations, and future research directions is provided. The proposed approach enables longterm security and supports a smooth transition toward quantum-safe distributed computing systems.
Post-quantum cryptography (PQC) is a critical area of research aimed at addressing the threat quantum computing poses to traditional cryptographic systems. It focuses on evaluating the efficiency, security, and practical performance of PQC algorithms through experimental analysis. This research supports the development of optimized cryptographic solutions, contributes to standardization efforts, and ensures secure and efficient implementations for a wide range of applications. Despite progress in PQC, gaps still exist in practical performance evaluations, particularly in resource-constrained environments. There is a lack of standardized comparisons, hindering the selection of suitable algorithms for specific use cases like IoT and cloud systems. Furthermore, research on scalability, integration challenges, and the trade-offs between security and efficiency remains insufficient. The methodology involves creating a comprehensive framework to evaluate various PQC algorithms, including lattice-based (e.g., Kyber, Dilithium), code-based (e.g., McEliece), and hash-based (e.g., SPHINCS+). These algorithms will be tested in diverse environments, from resource-constrained devices to high-performance infrastructures such as cloud platforms. Key metrics such as encryption/decryption speed, key sizes, memory usage, and computational efficiency will be measured, focusing on the trade-offs between security, efficiency, and scalability. The results will be benchmarked against standardized metrics to provide a clear understanding of each algorithm's suitability for real-world deployment. The findings indicate that lattice-based algorithms like Kyber offer a strong balance between security and efficiency but require considerable computational resources. Code-based algorithms like McEliece are highly secure but come with large key sizes and slower speeds. Hash-based schemes like SPHINCS+ provide strong security but are computationally expensive, making them less suitable for resource-limited systems. The highlights the importance of optimizing PQC algorithms according to specific application requirements, where the choice of algorithm must balance security, efficiency, and resource constraints, with continuous optimization needed to address evolving real-world demands.