In recent times, secure data transmission become crucial requirement because of increasing growth of threats and emergence of quantum computing technologies. However, existing Quantum Key Distribution-Advanced Encryption Standard-Least Significant Bit (QKD-AES-LSB) struggled with two main limitations such as restricted resistance to future quantum attacks because of dependence on classical encryption and vulnerability of static LSB steganography for improved Machine Learning (ML) approaches. To address these challenges, Quantum Key Distribution-Post-Quantum Cryptography-Adaptive Steganographic Encryption framework (QKD-PQC-ASE) is proposed. Primarily, secret data and cover images are gathered then quantum key is generated using E91 protocol. Next, post-quantum cryptographic key encapsulation is applied to strengthened the generated kay and ensure long-term quantum resistance. Further, secret data is encrypted employing quantum-resilient encryption mechanism and combined using cryptographic hashing. Furthermore, encrypted data is embedded in to cover image through quantum-randomness-guided adaptive steganography for resisting improved steganalysis attacks. Finally, proposed QKD-PQC-ASE framework obtains improved resistance against future quantum attacks and enhanced steganalysis by maintaining low computational overhead. Therefore, proposed QKD-PQC-ASE framework achieved greater results in terms of NPCR of 99.84 % and a UACI of$\mathbf{5 7. 9 2 \%}$which demonstrates efficiency of framework for secure and future-ready data encryption in quantum-aware communication environments.
In recent times, secure data transmission become crucial requirement because of increasing growth of threats and emergence of quantum computing technologies. However, existing Quantum Key Distribution-Advanced Encryption Standard-Least Significant Bit (QKD-AES-LSB) struggled with two main limitations such as restricted resistance to future quantum attacks because of dependence on classical encryption and vulnerability of static LSB steganography for improved Machine Learning (ML) approaches. To address these challenges, Quantum Key Distribution-Post-Quantum Cryptography-Adaptive Steganographic Encryption framework (QKD-PQC-ASE) is proposed. Primarily, secret data and cover images are gathered then quantum key is generated using E91 protocol. Next, post-quantum cryptographic key encapsulation is applied to strengthened the generated kay and ensure long-term quantum resistance. Further, secret data is encrypted employing quantum-resilient encryption mechanism and combined using cryptographic hashing. Furthermore, encrypted data is embedded in to cover image through quantum-randomness-guided adaptive steganography for resisting improved steganalysis attacks. Finally, proposed QKD-PQC-ASE framework obtains improved resistance against future quantum attacks and enhanced steganalysis by maintaining low computational overhead. Therefore, proposed QKD-PQC-ASE framework achieved greater results in terms of NPCR of 99.84 % and a UACI of57.92%which demonstrates efficiency of framework for secure and future-ready data encryption in quantum-aware communication environments.
The rapid expansion of the Internet of Things (IoT) has introduced unprecedented cybersecurity challenges, as traditional cryptographic methods struggle to provide both efficiency and quantum resistance in resource-constrained environments. This research introduces Adaptive Quantum Cryptography (AQC), a novel security framework that integrates Quantum Key Distribution (QKD), Post-Quantum Cryptography (PQC), Quantum Random Number Generators (QRNGs), and AI-driven dynamic adaptation to safeguard IoT networks against evolving cyber threats. Unlike classical encryption techniques such as RSA and ECC, which are vulnerable to quantum attacks, AQC leverages quantum mechanical principles—such as superposition, entanglement, and the no-cloning theorem—to ensure provably secure key exchange and data encryption. The proposed AQC system dynamically adjusts cryptographic protocols based on real-time network conditions, computational resources, and threat intelligence, optimizing security without imposing excessive overhead. Experimental evaluations demonstrate that AQC achieves a 70% improvement in key exchange efficiency, a 50% reduction in computational load, and a 95% resilience rate against quantum attacks compared to conventional encryption methods. Additionally, the integration of QRNGs enhances cryptographic key entropy, while AI-driven anomaly detection enables proactive threat mitigation. This framework is particularly suited for next-generation IoT applications, including smart grids, autonomous vehicles, and industrial automation, where security, scalability, and energy efficiency are critical. By combining quantum-resistant algorithms with adaptive security mechanisms, AQC provides forward secrecy, resistance to quantum adversaries, and robust authentication, ensuring long-term protection for IoT ecosystems in the post-quantum era. The findings underscore AQC’s potential as a foundational security architecture for future quantum-safe IoT networks.
Quantum computing threatens classical cryptography and the convergence of quantum key distribution (QKD), and steganography offers an unconditionally secure hybrid approach for postquantum communication. QKD ensures provable secrecy via quantum mechanics, while steganography conceals the existence of communication providing stealth and plausible deniability. This systematic review explores integrated frameworks that combine QKD with classical and quantum steganographic techniques to enhance confidentiality, integrity, and undetectability. The study categorizes existing hybrid models and evaluates their performance using metrics such as quantum bit error rate (QBER), entropy, and imperceptibility. It examines quantum steganographic protocols including quantum LSB, entangled‐state hiding, and covert key transmission, analyzing their resilience against quantum noise and steganalysis. Despite promising simulation tools and real‐time QKD implementations, challenges remain in scalability, interoperability, and formal security guarantees. This review identifies key limitations in current systems and highlights future directions for developing robust, scalable, and stealth‐aware quantum–classical security frameworks. To the best of current knowledge, this is the first systematic synthesis of hybrid QKD–steganography frameworks offering a novel taxonomy and critical analysis to advance secure communication infrastructures in the postquantum era.
In the realm of cybersecurity, the demand for robust encryption and secure data hiding techniques has intensified with the proliferation of digital communication and sensitive information exchange. This paper explores integration of QC advancements for enhancing the security of two critical cryptographic applications: Advanced Encryption Standard (AES) encryption and Least Significant Bit (LSB) image steganography. Quantum computing introduces the concept of qubits, which harness quantum mechanical phenomena to perform computations that classical computers struggle to achieve efficiently. By leveraging qubits, AES encryption can potentially benefit from enhanced key generation and encryption processes, thereby strengthening data confidentiality against conventional and future quantum attacks. Additionally, this paper investigates the application of quantum-inspired techniques to optimize the LSB method in image steganography. LSB embedding involves hiding data within LSB of image pixels, technique vulnerable to statistical attacks. Quantum-inspired approaches aim to mitigate these vulnerabilities by improving embedding efficiency and robustness without compromising image quality. Through theoretical analysis and simulation studies, this research evaluates the feasibility and potential benefits of integrating quantum computing into AES encryption and LSB steganography. The findings underscore the promise of quantum-enhanced methods in fortifying data security across digital platforms, laying the groundwork for future advancements in quantum cryptography and information hiding techniques.
This research introduces a novel cryptographic system that enhances the security of steganographic images by integrating Quantum Key Distribution (QKD) with traditional encryption. Using the E91 QKD protocol, it generates a shared secret key between parties, leveraging quantum entanglement to provide superior protection against eavesdropping. The quantum key is then hashed with the Secure Hash Algorithm (SHA) to produce a fixed-length, high-entropy key for symmetric encryption . The Advanced Encryption Standard (AES) is employed to encrypt steganographic images, which conceal critical data within digital images, adding an extra layer of security through obscurity. Experiments with images of varying resolutions (64 × 64 to 512 × 512 pixels) show consistent encryption performance. The encrypted images exhibit high randomness, with an average entropy of 7.9929. Differential attack resilience is demonstrated by a Number of Pixels Change Rate (NPCR) averaging 99.6928% and a Unified Average Changing Intensity (UACI) of 56.1549%. The average E91 protocol key generation time is 5.78 s with a key rate of 7.43 bps. Encryption and decryption times for test images are 0.00149 and 0.00175 s, respectively. This research combines quantum and classical cryptography with steganography, providing a robust security framework highly resistant to both quantum and classical threats.
The Hybrid approach in Quantum Cryptography creates adaptable security model which provides the safest Communication in the emerging quantum era. The development of quantum computing raise questions about the long-term security. Traditional algorithms, such as RSA, ECC, and Diffie-Hellman, which is seemed computationally secure but it can be effectively solved by quantum algorithms such as Shor's and Grover's. This problem leads to the origination of two key trends in current studies, namely Post-Quantum Cryptography (PQC), designing mathematical approaches to encryption resistant to quantum attacks; Quantum Key Distribution (QKD) using the principles of quantum mechanics to assure security in communications. Accordingly, this research proposes a hybrid security framework including reliable data encryption and authentication using PQC, combined with the safe key- exchange method of QKD. The model is implemented in Python, Qiskit, and PQClean's Kyber and Dilithium algorithms to show how these two paradigms can cooperate toward quantum- resilient communication. To present the system performance, key exchange efficiency, computational overhead, and security strength have been considered. According to the results, this hybrid approach gives superior defense against quantum threats while maintaining practical effectiveness for real-world applications such as cloud security, 6G networks, and the Internet of Things.
The rapid proliferation of Internet of Things (IoT) devices presents critical cybersecurity challenges, as traditional cryptographic methods often fail to provide both robust security and operational efficiency in resource-constrained environments. This paper introduces Adaptive Quantum Cryptography (AQC), a novel framework designed to secure next-generation IoT networks against evolving classical and quantum-computing threats. The AQC framework synergistically integrates Quantum Key Distribution (QKD) for unbreakable key exchange, Quantum Random Number Generators (QRNGs) for high-entropy key generation, and Post-Quantum Cryptography (PQC) for quantum-resistant data encryption. A key feature of the system is its dynamic adaptation mechanism, which leverages artificial intelligence to intelligently select and adjust cryptographic protocols in real-time based on current network conditions, device computational capabilities, and identified threat levels. This ensures optimal security without imposing excessive overhead on IoT devices. Our comprehensive experimental evaluation demonstrates that the AQC framework significantly outperforms classical techniques, achieving a 70% improvement in key exchange efficiency, a 50% reduction in computational load, and a 95% resilience rate against quantum-based attacks. By providing forward secrecy and robust authentication, the proposed AQC framework offers a scalable, energy-efficient, and future-proof security solution, paving the way for resilient and trustworthy IoT ecosystems in the post-quantum era.