ABSTRACT The rapid evolution of quantum computing poses a significant threat to classical cryptographic systems like Rivest‐Shamir‐Adleman (RSA) and Elliptic Curve Cryptography (ECC), which rely on the computational hardness of problems such as integer factorization and discrete logarithms. Quantum algorithms such as Shor's algorithm can solve these problems quickly, which undermines the foundations on which classical cryptography relies. Quantum Key Distribution (QKD) is an alternative to the classical methods, which promises information‐theoretic security based on quantum mechanics. Currently, there are existing QKD protocols, including BB84, B92, E91, and GHZ, all of which exhibit various real‐world limitations. For example, these QKD protocols can be vulnerable to a variety of side‐channel attacks (e.g., detector blinding, photon‐number‐splitting) and neglect to consider fluctuating network conditions. Current QKD protocols also fail to accommodate scalability for many‐to‐many or noise‐limited scenarios. Many implementations of the existing QKD protocols and other common forms of networks remain static, relying on arbitrary decisions of fixed values that yield simple linear conclusions that can be predicted and targeted in the real‐world environment. To address these omissions, we propose a new framework for dynamic or adaptive hybrid QKD in which we incorporate BB84, B92, E91, and GHZ into one common approach with all protocols selected based on a probability‐weighted distribution of (0.3, 0.2, 0.3, 0.2). In the hybrid QKD implementation, the probability weights of protocol selection are assigned with partiality toward BB84, E91, B92, and GHZ, respectively. This may also introduce a higher variety of protocols and diversity in approaches that will further limit cross‐protocol possibilities of attack vectors, while increasing the possible flexibility of adaptability in attacked situations. In addition, we incorporate an artificial intelligence (AI)‐based optimization module using a neural network to evaluate local environmental noise and quantum bit error rate (QBER) in real time. It adjusts protocol selection probabilities dynamically based on both historical and live operational data to optimize throughput while maintaining low error rates. The system architecture supports modular and parallel operation and has been mapped out and designed to be scalable and compatible with future quantum networks. We test our system using IBM's Qiskit AerSimulator utilizing a 14‐qubit register with 100 rounds of a 1% depolarization noise model, which significantly outperformed static hybrids such as Chen et al. in terms of both key rate and QBER. Our system consistently produced an average QBER of 0.02 and a key generation rate of 12 bits per round. E91 consistently produced CHSH violating confirming the fidelity of the entanglement, while BB84 displayed no QBER on all rounds. This work demonstrates the first fully integrated, AI‐assisted, dynamic hybrid QKD system. It includes all advantageous features of a QKD protocol: the dynamic adaptability of the protocol allows for a performance driven environment, the use of entangled states provides increased security, and a bottom‐up approach to real‐time optimization creating a robust, scalable, and agnostic system to any hardware used by post‐quantum cryptographic infrastructures.
ABSTRACT The rapid evolution of quantum computing poses a significant threat to classical cryptographic systems like Rivest‐Shamir‐Adleman (RSA) and Elliptic Curve Cryptography (ECC), which rely on the computational hardness of problems such as integer factorization and discrete logarithms. Quantum algorithms such as Shor's algorithm can solve these problems quickly, which undermines the foundations on which classical cryptography relies. Quantum Key Distribution (QKD) is an alternative to the classical methods, which promises information‐theoretic security based on quantum mechanics. Currently, there are existing QKD protocols, including BB84, B92, E91, and GHZ, all of which exhibit various real‐world limitations. For example, these QKD protocols can be vulnerable to a variety of side‐channel attacks (e.g., detector blinding, photon‐number‐splitting) and neglect to consider fluctuating network conditions. Current QKD protocols also fail to accommodate scalability for many‐to‐many or noise‐limited scenarios. Many implementations of the existing QKD protocols and other common forms of networks remain static, relying on arbitrary decisions of fixed values that yield simple linear conclusions that can be predicted and targeted in the real‐world environment. To address these omissions, we propose a new framework for dynamic or adaptive hybrid QKD in which we incorporate BB84, B92, E91, and GHZ into one common approach with all protocols selected based on a probability‐weighted distribution of (0.3, 0.2, 0.3, 0.2). In the hybrid QKD implementation, the probability weights of protocol selection are assigned with partiality toward BB84, E91, B92, and GHZ, respectively. This may also introduce a higher variety of protocols and diversity in approaches that will further limit cross‐protocol possibilities of attack vectors, while increasing the possible flexibility of adaptability in attacked situations. In addition, we incorporate an artificial intelligence (AI)‐based optimization module using a neural network to evaluate local environmental noise and quantum bit error rate (QBER) in real time. It adjusts protocol selection probabilities dynamically based on both historical and live operational data to optimize throughput while maintaining low error rates. The system architecture supports modular and parallel operation and has been mapped out and designed to be scalable and compatible with future quantum networks. We test our system using IBM's Qiskit AerSimulator utilizing a 14‐qubit register with 100 rounds of a 1% depolarization noise model, which significantly outperformed static hybrids such as Chen et al. in terms of both key rate and QBER. Our system consistently produced an average QBER of 0.02 and a key generation rate of 12 bits per round. E91 consistently produced CHSH violating confirming the fidelity of the entanglement, while BB84 displayed no QBER on all rounds. This work demonstrates the first fully integrated, AI‐assisted, dynamic hybrid QKD system. It includes all advantageous features of a QKD protocol: the dynamic adaptability of the protocol allows for a performance driven environment, the use of entangled states provides increased security, and a bottom‐up approach to real‐time optimization creating a robust, scalable, and agnostic system to any hardware used by post‐quantum cryptographic infrastructures.
Secure communication has become essential due to the rapid increase in cyber-attacks and data security threats in modern networks. Traditional communication systems mainly rely on classical security methods, which may become vulnerable to advanced attacks. Quantum Key Distribution (QKD) improves secure communication by generating cryptographic keys using quantum principles, making key interception extremely difficult. In this work, a Quantum Random Number Generator (QRNG) is integrated with classical communication to develop a hybrid quantum-classical communication framework. The QRNG generates highly random bits that improve authentication, randomness, and key security. The proposed system compares three QKD protocols: BB84, B92, and E91 using different bit sizes of 8000, 10000, and 13000 bits. The protocols are evaluated using important metrics such as QBER, key rate, entropy, erasure rate, throughput, and correlation. Experimental results show that all protocols achieved entropy values close to 1 and correlation values near zero, indicating strong randomness and secure key generation. Among the evaluated protocols, E91 achieved lower QBER values and higher key rates, while BB84 showed stable and reliable performance. B92 produced comparatively higher error rates under similar conditions. The throughput remained nearly 278–281 bits/sec across all experiments. A ranking-based analysis confirmed that E91 provides the best balance between security, efficiency, and communication performance, making it suitable for future quantum-secure communication systems.
Quantum Key Distribution (QKD) is increasingly recognized as a robust solution to the vulnerabilities posed by quantum computing to classical encryption systems. This paper presents a comprehensive investigation of the BB84 protocol, the foundational QKD scheme, through simulated quantum communication using IBM’s Qiskit framework. The study models quantum key exchange under both ideal and adversarial conditions, including channel noise and intercept-resend attacks. The Quantum Bit Error Rate (QBER) was measured as a function of noise intensity and eavesdropping, confirming that QBER increases predictably in compromised channels. A threshold of 11% QBER was used to determine the viability of secure key generation. Final key retention rates were analyzed across multiple channel scenarios, revealing BB84’s sensitivity to both photon loss and adversarial interference.\n\nSecurity vulnerabilities such as photon-number-splitting and detector blinding were assessed, and countermeasures including decoy-state protocols and authenticated classical channels were proposed. Four key performance graphs were generated to visualize system behavior under realistic operational conditions. The results support BB84’s theoretical advantage in ensuring information-theoretic security while acknowledging real-world limitations in transmission range and hardware reliability. The paper concludes by addressing future improvements in QKD systems, including satellite-based distribution, quantum repeaters, and device-independent implementations. Through simulation-driven analysis, this study validates BB84 as a practical defense against quantum-enabled attacks and underscores the need for continued development and standardization in post-quantum cryptographic infrastructure.
The rapid advancement of quantum computing poses a significant threat to classical cryptographic systems that form the backbone of modern digital security.Algorithms such as RSA and ECC, which rely on the computational difficulty of integer factorization and discrete logarithm problems, become vulnerable to quantum attacks, particularly Shor's algorithm.This project presents a comprehensive Quantum Key Distribution (QKD) Simulator that implements the BB84 and E91 protocols using IBM's Qiskit quantum computing framework, providing an interactive platform for understanding, simulating, and analyzing quantum-safe key exchange mechanisms.The simulator features a full-stack architecture with a FastAPI backend powered by Python and Qiskit for quantum circuit execution, and a React 19 frontend with TypeScript for interactive visualization.The BB84 protocol implementation supports configurable qubit counts, multiple measurement bases (Z, X, and Diagonal), Eve's intercept-resend attack simulation with adjustable interception rates, and Quantum Bit Error Rate (QBER) calculation with a security threshold of 8.5%.The E91 protocol implementation uses entangled Bell state pairs with configurable measurement angles, CHSH inequality violation testing for quantum security verification, and reverse gate anti-eavesdropping mechanisms.Additionally, the system includes an AES encryption module that uses quantum-generated keys from BB84 and E91 simulations to perform AES-128, AES-192, and AES-256 encryption, with privacy amplification for keys shorter than the required length.A simulation history system with SQLite and PostgreSQL support enables experiment tracking, comparison, and analysis.The project demonstrates the practical application of quantum mechanics principles to cryptographic security and serves as an educational tool for understanding the transition from classical to quantum-safe cryptography.
As the limitations of classical cryptographic systems become increasingly evident in the face of advancing quantum algorithms, Quantum Key Distribution (QKD) emerges as a vital paradigm for securing information in next-generation networks. This paper explores the theoretical foundations and protocol architectures underpinning QKD, including BB84, E91, and newer hybrid approaches designed for scalable integration into existing infrastructures. Performance metrics such as key generation rate, error thresholds, and resistance to various attack models are critically examined across both fiber-optic and free-space implementations. Furthermore, the study delves into real-world deployment challenges—ranging from synchronization errors and quantum channel noise to cost-efficiency and interoperability with classical systems. By offering a comparative analysis and proposing optimization strategies, this work aims to pave the way for robust quantum-secure communication protocols suited for large-scale, heterogeneous network environments.
Quantum key distribution (QKD) protocols fall into two main categories: entanglement‐based and non‐entanglement‐based. Although entanglement‐based QKD offers strong security, it theoretically generates fewer keys with the same number of logical qubits. In contrast, the non‐entanglement‐based method produces more keys but with reduced security. To address these concerns, in this article, we present a novel hybrid QKD protocol that combines both approaches to optimize security and key generation. We introduce a dynamic system that integrates a three‐particle entangled Greenberger–Horne–Zeilinger (GHZ)‐state method with the two‐particle BB84 QKD protocol, using a quantum superposition state to probabilistically switch between them. The GHZ state component leverages strong three‐particle entanglement correlations for enhanced security, while the BB84 component offers simplicity and potentially a higher number of key generation. This protocol was implemented and simulated using IBM’s Qiskit and IBM Quantum Platform; our approach demonstrates 63.48% higher number of key generation compared to the E91 protocol, although 37. 33% lower than the standalone BB84 protocol while maintaining robust security and being less prone to quantum bit error rate (QBER). The results and security discussion show that this combined method effectively balances the trade‐offs inherent in QKD systems, offering a flexible framework adaptable to varying channel conditions and security requirements.
Quantum computing advances pose a serious threat to conventional public-key cryptographic systems such as RSA and elliptic curve cryptography as quantum algorithms may undermine the computational assumptions that guaranty their security. This challenge has driven the development of quantumsafe security approaches among which Quantum Key Distribution (QKD) represents a fundamentally different paradigm based on quantum mechanical principles rather than mathematical complexity. This paper presents a structured review of recent progress in QKD based on a systematic analysis of literature between 2020 and 2025, we examine core protocols including discrete-variable, continuous-variable, measurement-deviceindependent, and twin-field approaches, while also discussing their relationship with post-quantum cryptography as a complementary strategy for future secure communication systems. We provide a unified comparison framework to support practical design and policy decisions by organizing protocols and implementations along deployment dimensions. The study analyze theoretical foundations, implementation technologies across fiber, free-space, satellite, and integrated photonic platforms, and key performance trade-offs involving scalability, security robustness, and deployment feasibility. Findings indicate substantial progress in transitioning QKD from laboratory research toward practical implementations, supported by advances in network architectures, integrated hardware and hybrid cryptographic designs. The comparative analysis will highlight distinct strengths and limitations among protocol families and emphasize the potential of combining QKD with post-quantum cryptographic methods to enhance resilience. Remaining challenges including scalability constraints, implementation-level vulnerabilities, performance limitations over long distances, and integration with existing communication infrastructures are critically discussed. Finally, emerging research directions such as quantum repeaters, hybrid quantum-classical security models, and exploratory directions such as artificial intelligence-assisted optimizations are identified as key factors in enabling the evolution of QKD toward largescale quantum-secure networking.