The quantum computing continues to advance, the security of conventional cryptographic systems faces significant risks, prompting rapid developments in post-quantum cryptography (PQC). This paper presents a series of targeted improvements to the Falcon digital signature scheme in post-quantum cryptography. The analysis of Falcon’s framework, several areas can be identified where optimizations could enhance performance. This lowers the computing overhead while maintaining the algorithm’s resilience to quantum attacks by using GPU offloading, parameter recalibration, and other optimization strategies. Experimental evaluation shows an approximate 11% reduction in execution time without compromising the security guaranteed by the original method. These enhancements make it more practical for resource-constrained environments.
The quantum computing continues to advance, the security of conventional cryptographic systems faces significant risks, prompting rapid developments in post-quantum cryptography (PQC). This paper presents a series of targeted improvements to the Falcon digital signature scheme in post-quantum cryptography. The analysis of Falcon’s framework, several areas can be identified where optimizations could enhance performance. This lowers the computing overhead while maintaining the algorithm’s resilience to quantum attacks by using GPU offloading, parameter recalibration, and other optimization strategies. Experimental evaluation shows an approximate 11% reduction in execution time without compromising the security guaranteed by the original method. These enhancements make it more practical for resource-constrained environments.
The transition to post-quantum cryptography (PQC) marks a pivotal shift in ensuring digital security, prompted by the potential of quantum computers to compromise classical systems such as Rivest-Shamir-Adlema and elliptic-curve cryptography. In response, NIST has standardized three foundational PQC algorithms: Module-lattice-based Key-encapsulation Mechanism for key establishment; Module-lattice-based Digital Signature, and Stateless Hash-based Digital Signature algorithms for digital signatures. Meanwhile, FALCON and Hamming Quasi-cyclic (HQC) schemes, both selected as finalists, are expected to join the standards soon. This paper presents a comprehensive survey of these NIST-selected PQC standards, with a dual focus on software implementations and hardware architecture designs. We analyze their mathematical frameworks, distinctive features, and optimization strategies related to performance, security, and resource efficiency. The software review examines algorithmic complexity, memory usage, and programming considerations, while the hardware review discusses FPGA and ASIC implementations, emphasizing modular arithmetic, polynomial operations, and resource efficiency challenges. A comparative analysis highlights the strengths and trade-offs of each algorithm, offering insights into their applicability across various platforms-from resource-constrained internet of things devices to high-performance computing environments. This study provides a foundational understanding of NIST’s selected PQC standards and their practical deployment in securing the post-quantum era.
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 presents a potential threat to conventional cryptographic systems, prompting the urgent need for post-quantum cryptography (PQC) solutions. However, the complexity of these cryptographic protocols often leads to inefficiencies in performance, hindering their widespread adoption. This paper explores the integration of machine learning (ML) techniques to optimize the performance of post-quantum cryptographic protocols. We propose an innovative framework where ML algorithms are leveraged to enhance the efficiency of key generation, encryption, decryption, and signature processes in PQC schemes. By utilizing data-driven approaches such as reinforcement learning and neural networks, we aim to reduce computational overhead and improve latency, while maintaining the robustness and security of post-quantum algorithms. Experimental results demonstrate significant performance improvements over traditional optimization methods, showcasing the potential of ML in advancing the practicality of PQC protocols. This work lays the foundation for a new class of cryptographic systems capable of withstanding quantum threats while maintaining high operational efficiency.
Conventional public-key cryptographic systems are increasingly threatened by advances in quantum computing, accelerating the need for robust post-quantum cryptographic solutions. Among these, Falcon, a compact lattice-based digital signature scheme, has emerged as a leading candidate in the NIST post-quantum standardization process due to its efficiency and theoretical security grounded in hard lattice problems. This work introduces Falcon-M, a modified version of the Falcon algorithm that significantly reduces implementation complexity. It does so by replacing Falcon’s intricate trapdoor-based key-generation mechanism with a simplified approach that utilizes randomized polynomial Gaussian sampling and fast Fourier transform (FFT) operations. Falcon-M incorporates SHA-512 hashing and discrete Gaussian sampling to preserve cryptographic soundness and statistical randomness while maintaining the core structure of Falcon’s signing and verification processes. We formally specify the Falcon-M algorithm, provide an updated pseudocode, and offer a comparative analysis with the original Falcon in terms of algorithmic complexity, security assumptions, and implementation overhead. Additionally, we present formal lemmas and theorems to ensure correctness and define theoretical bounds on forgery resistance. Although Falcon-M does not rely on a formal cryptographic trapdoor, we demonstrate that it achieves strong practical security based on assumptions related to the Short Integer Solution (SIS) problem. Falcon-M is thus well-suited for lightweight post-quantum applications, particularly in resource-constrained environments, such as embedded systems and Internet-of-Things (IoT) platforms.
The emergence of quantum computing is expected to break many conventional cryptographic algorithms currently used for authentication and secure communication. Existing security mechanisms in Next Generation Networks (NGNs), including 5G, IoT, smart healthcare, and cloud-based systems, are increasingly vulnerable to future quantum attacks. This research presents a lightweight and efficient Post-Quantum Cryptography (PQC) based authentication framework specifically designed for next generation network environments. The proposed framework combines quantum-resistant cryptographic techniques with optimized authentication procedures to provide secure identity verification, confidential communication, and attack resistance with minimal computational complexity. The model emphasizes reduced overhead, faster authentication response, and scalability for resource-constrained devices. Security analysis shows that the framework can effectively defend against replay attacks, impersonation attacks, session hijacking, and quantum-based cryptanalytic threats. Experimental evaluation indicates that the proposed approach achieves improved security performance while maintaining low latency and reduced resource consumption, making it suitable for practical deployment in future intelligent communication networks.
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.