Abstract The imminent threat posed by quantum computing to classical cryptographic systems necessitates the development of quantum-resistant, efficient, and scalable encryption techniques, especially for real-time distributed optimization networks critical to national infrastructure. This study introduces a novel lightweight post-quantum cryptographic algorithm tailored for secure real-time decision-making in decentralized systems such as smart grids, autonomous transport, and defense communication networks. This study proposes a lattice-based encryption scheme optimized for low-latency and bandwidth-constrained environments, integrating a parameterized Learning With Errors (LWE) framework with a compressed key encapsulation mechanism (KEM). The cryptographic algorithm is coupled with an adaptive distributed optimization protocol that dynamically adjusts computation and communication loads across agents to maintain performance under cryptographic overhead. The method is rigorously analyzed in terms of computational complexity, security assumptions, and operational feasibility. Simulation experiments are conducted over dynamic networks modeled on real-world distributed control systems, comparing performance metrics such as encryption latency, decision throughput, and fault tolerance against state-of-the-art schemes. Results demonstrate significant improvements in end-to-end delay, with cryptographic integrity maintained under adversarial conditions, establishing the scheme’s applicability for post-quantum real-time systems. The contributions of this work bridge the critical research gap between post-quantum cryptography and real-time optimization, reinforcing secure decision-making in systems of national interest.
Abstract The imminent threat posed by quantum computing to classical cryptographic systems necessitates the development of quantum-resistant, efficient, and scalable encryption techniques, especially for real-time distributed optimization networks critical to national infrastructure. This study introduces a novel lightweight post-quantum cryptographic algorithm tailored for secure real-time decision-making in decentralized systems such as smart grids, autonomous transport, and defense communication networks. This study proposes a lattice-based encryption scheme optimized for low-latency and bandwidth-constrained environments, integrating a parameterized Learning With Errors (LWE) framework with a compressed key encapsulation mechanism (KEM). The cryptographic algorithm is coupled with an adaptive distributed optimization protocol that dynamically adjusts computation and communication loads across agents to maintain performance under cryptographic overhead. The method is rigorously analyzed in terms of computational complexity, security assumptions, and operational feasibility. Simulation experiments are conducted over dynamic networks modeled on real-world distributed control systems, comparing performance metrics such as encryption latency, decision throughput, and fault tolerance against state-of-the-art schemes. Results demonstrate significant improvements in end-to-end delay, with cryptographic integrity maintained under adversarial conditions, establishing the scheme’s applicability for post-quantum real-time systems. The contributions of this work bridge the critical research gap between post-quantum cryptography and real-time optimization, reinforcing secure decision-making in systems of national interest.
The rapid advancement of quantum computing poses a critical threat to classical public-key cryptographic systems widely used in defense communication infrastructures, while the practical deployment of post-quantum cryptography (PQC) remains constrained by excessive key sizes, computational overhead, and energy consumption in bandwidth- and latency-sensitive military environments. This study aims to develop and evaluate a quantum-inspired multi-objective optimization framework to enhance the operational feasibility of standardized PQC schemes without compromising cryptographic security. The proposed method applies a Quantum Genetic Algorithm (QGA) to optimize configuration parameters of CRYSTALS-Kyber and CRYSTALS-Dilithium by simultaneously balancing security strength, computational performance, resource efficiency, and deployability. Experiments were conducted using official NIST test vectors and defense-oriented communication scenarios, with performance evaluated across encryption and signature latency, throughput, key and signature sizes, memory footprint, and energy consumption, while security was validated against classical and quantum attack models. The results demonstrate that the optimized configurations achieve key and signature size reductions of up to 10.3%, throughput improvements of up to 15.5%, and energy consumption reductions of up to 12.5% compared to baseline NIST implementations, while fully maintaining NIST security levels and robust resistance to quantum adversaries. These improvements significantly enhance the suitability of PQC for tactical radios, satellite communications, and resource-constrained defense platforms. The findings indicate that quantum-inspired multi-objective optimization is a critical enabler for transitioning post-quantum cryptography from theoretical security constructs to deployable, mission-ready solutions in real-world defense systems.
The advent of quantum computing poses an existential threat to contemporary cryptographic standards, particularly those securing decentralized blockchain networks and cloud infrastructures.Classical public-key cryptosystems such as RSA, ECC, and DH, which rely on factorization and discrete logarithm problems, are rendered obsolete by Shor's algorithm, necessitating the transition toward post-quantum cryptographic (PQC) solutions.This study explores the integration of PQC algorithms, including lattice-based, hash-based, code-based, multivariate, and isogeny-based cryptographic mechanisms, within blockchain-ledger technologies and cloud architectures to ensure long-term security against quantum adversaries.A comparative analysis is conducted to evaluate computational efficiency, key size implications, communication overhead, and security resilience under quantum attack models.The research highlights the adaptation of PQC within blockchain consensus mechanisms, smart contract execution, and cryptographic primitives such as digital signatures, zero-knowledge proofs, and secure multi-party computation (MPC).Additionally, it examines the impact of PQC on cloud security, addressing challenges in quantum-safe key exchange protocols, homomorphic encryption for secure computations, and cross-platform interoperability within hybrid quantum-classical cloud ecosystems.Real-world implementations and benchmarking data provide insights into the feasibility of large-scale adoption, shedding light on standardization efforts by NIST and industry consortia.The study concludes with future directions, emphasizing the need for efficient PQC algorithm optimization, lightweight cryptographic frameworks for IoT-driven blockchain applications, and scalable post-quantum identity management systems.By establishing quantum-resistant security frameworks, this research underscores the imperative need for early adoption to mitigate cryptographic vulnerabilities in the impending post-quantum era.
The rapid development of quantum computing presents a substantial threat to traditional cryptographic algorithms, particularly those relying on mathematical problems such as integer factorization and elliptic curve operations. As a response, the cryptographic community has accelerated the design of post-quantum cryptographic schemes that can withstand attacks from both classical and quantum computers. However, many of these new schemes exhibit inherent trade-offs between performance, key sizes, and implementation complexity. To address this, we propose a novel hybrid cryptographic framework tailored for secure and efficient data transmission in future quantum-aware environments. The proposed system combines three algorithmic paradigms: a lattice-based encryption method for fast and lightweight data protection, a hash-based signature mechanism for authenticity, and a code-based key exchange method to ensure session confidentiality. This layered integration is designed to capitalize on each algorithm’s strengths while mitigating individual limitations. The system is implemented using modular components in a testbed simulating real-world deployments, and its performance is benchmarked across multiple metrics including encryption latency, signature generation time, key sizes, and throughput. Comparative results indicate that the hybrid approach outperforms monolithic schemes in critical areas such as execution time and cryptographic strength under quantum adversary models. The findings support the practicality of using multiple post-quantum primitives in tandem to build robust communication systems. This research contributes a realistic implementation and evaluation of post-quantum security models and highlights key directions for future research and standardization efforts as the global transition to quantum-safe infrastructure begins.
the rapid advancement of quantum computing introduces substantial risks to classical cryptographic algorithms that rely on number-theoretic problems, such as the Rivest–Shamir–Adleman algorithm and elliptic curve cryptography. These cryptographic primitives are susceptible to polynomial-time quantum algorithms like those proposed by Shor and Grover, thereby endangering the security of contemporary digital infrastructures. In light of these emerging threats, the global cryptographic community is prioritizing the development and deployment of quantum-resistant cryptographic techniques. These include diverse algorithmic families such as those based on lattices, hash functions, error-correcting codes, and multivariate polynomials. Each approach exhibits distinct trade-offs in terms of computational performance, key length, signature size, and long-term resilience. This paper introduces a hybrid cryptographic framework optimized for specific application domains, particularly those with limited computational and energy resources. The proposed architecture strategically combines lattice-based encryption, hash-based digital signatures, and code-based key encapsulation mechanisms to form a unified model for secure data transmission. The architecture is implemented and evaluated across heterogeneous computing environments, including low-power embedded systems and Field-Programmable Gate Arrays. Experimental metrics such as execution latency, computational overhead, memory consumption, and energy efficiency are assessed and benchmarked against traditional single-algorithm deployments. The findings demonstrate that the hybrid approach maintains strong quantum resistance while significantly reducing performance penalties, making it suitable for mobile platforms, Internet of Things environments, and real-time communication systems. Future work should emphasize further fine-tuning for specific industrial domains, standardization of hybrid cryptographic protocols, and integration with artificial intelligence-based adaptive security layers to ensure sustainability in the approaching quantum era.
It is also worth noting that the implementation of quantum computing has been a big threat to the classical cryptographic algorithms that are popular in secure networked systems. PostQuantum Cryptography (PQC) has come to play as one of the viable answers to this issue because it has the capacity to resist quantum-enabled attacks. In this paper, the author offers a detailed performance analysis of post-quantum cryptographic algorithms, lattice-based encryption which is based on the Learning with Errors (LWE) principle, and hashbased digital signatures which is based on SPHINCS+. An experimental environment was created that is controlled by using specific performance measures, such as time of key generation, the latency of encryption and decryption, amount of memory, and the size of keys and ciphertext. To determine the suitability of PQC in guaranteeing confidentiality, integrity, and authenticity over insecure channels, secure network communication was emulated. Through experimental findings, it has been shown that the lattice-based generation of keys has greater overhead in terms of computation and memory, but the encryption, decryption and signature processes have feasible limits. The results validate the practicability of the post-quantum cryptography mechanisms implementation in the practical secure network systems and the trade-off between the increased quantum resistance and the resource consumption.
The emergence of quantum computing challenges traditional security mechanisms, particularly in heterogeneous and resource-constrained IoT and smart environments that must satisfy DN25 requirements. This work introduces a reinforcement learning-driven model for the adaptive selection and orchestration of cryptographic algorithms. Acting as an intelligent decision layer, the system observes contextual, network, and operational metrics to recommend or enforce configurations combining classical schemes, post-quantum cryptography, and Quantum Key Distribution when available. The selection problem is formulated as a Markov Decision Process with state and action spaces aligned with protocol control flows and is embedded into a security middleware with negotiation and fallback mechanisms to ensure interoperability and policy compliance without modifying application logic. Experimental results demonstrate that the model dynamically adjusts key lengths, algorithm families, and security policies according to risk and resource conditions, increasing post-quantum cryptography and Quantum Key Distribution usage by up to 33.4% and 23.9% in high-risk scenarios while favoring low-latency classical or hybrid options for less critical traffic. The system achieves success rates above 78% while maintaining stable latency and resource usage during extended operation.