This paper presents Quantum Gatekeeper, a context-bound image steganography framework where successful payload recovery depends on both cryptographic decryption and the reconstruction of a precise extraction path. The system integrates lossless least significant bit (LSB) embedding with a deterministic variational quantum circuit (VQC)-derived gate key, multi-factor contextual binding, and authenticated encryption. Payload extraction is contingent upon four requisite factors: a password, a shared secret, a user-supplied context string, and a reference image signature. Any deviation in these factors causes the system to read from an incorrect pixel sequence or fail authentication, resulting in silent rejection rather than partial disclosure. The proposed method derives a gatecontrolled extraction key from a seed-conditioned variational circuit, with parameters generated via cryptographic hash expansion and context-dependent image features. To ensure encode/decode consistency, the cryptographic key path is generated via exact statevector simulation; concurrently, IBM superconducting quantum hardware is utilized to evaluate the statistical behavior of the circuit family under physical noise. We introduce a dual-region image layout to resolve the nonce bootstrapping dependency, separating header recovery from payload recovery through independently derived keys. Experimental results confirm successful end-to-end message embedding and recovery on PNG images, demonstrating deterministic success under correct conditions and failure otherwise. The framework supports both text and image payloads; in the image-in-image configuration, a secret image is resized to a fixed resolution prior to embedding, enabling exact pixel-level recovery under correct contextual reconstruction.
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.
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
57.92%which demonstrates efficiency of framework for secure and future-ready data encryption in quantum-aware communication environments.
This paper presents a communication algorithm in which a grayscale image, shared between two parties, can be used to transmit a secret message, by applying the idea introduced in the B92 quantum protocol. The least significant qubits of the pixels’ representation in certain regions of the image are used. With the help of a server, the algorithm generates a random message, which can further act as a secret key for cryptographic algorithms in order to secure the data that two parties might want to exchange later on. The chosen representation of the image is NEQR (novel enhanced quantum representation) and the platform used for testing the described idea is IBM Quantum Experience, along with the open-source Python framework called Qiskit. This solution allows users to design, implement quantum circuits (containing various quantum gates), and simulate them using real devices and local simulators. An implementation using this platform for a sample image and the corresponding results are also presented in this paper.
As the world is transitioning towards the quantum era, this research presents the Quantum Key Distribution Inspired Image Encryption (QKDIE) algorithm, an image encryption and decryption framework that leverages the BB84 quantum key distribution (QKD) protocol to enhance the security of image transmission. BB84 ensures secure key exchange through the quantum bit error rate (QBER) monitoring. A QBER of approximately
1.0% was consistently achieved across all the experiments and well below the 11% security abort threshold. The BB84 sifted key is used to derive a 256-bit ChaCha20 stream cipher key via SHA-256, providing formally IND-CPA secure encryption with a unique nonce per session. The encryption pipeline implements four successive layers: Fisher-Yates pixel permutation for spatial scrambling, a key-dependent nonlinear S-box substitution for per-pixel confusion, an invertible CBC-style row-column diffusion layer for inter-pixel avalanche propagation, and ChaCha20 stream encryption for quantum seeded bitwise transformation. The proposed method is evaluated through cryptographic security metrics including UACI, NPCR, Shannon Entropy, pixel correlation, chi-square uniformity test, avalanche effect, and known-plaintext attack simulation, alongside decryption fidelity metrics including MSE, PSNR, SSIM, and NIQE. Experimental results across four test images demonstrate UACI values of
33.46% –
36.59% , NPCR values of
99.59% –
99.63% , Shannon entropy of 7.9968–7.9995 bits per pixel, and near-zero pixel correlation in all spatial directions. All four images passed the chi-square uniformity test (values 217.77–283.94, critical value 293.25). The avalanche test confirmed
99.60% –
99.61% pixel change rate and
50.01% –
50.05% bit-level change rate with a single-bit key perturbation, satisfying the strict avalanche criterion. KPA simulation confirmed keystream independence across sessions (
47.27% –
51.95% bit match, indistinguishable from random chance). Perfect decryption was achieved in all cases (MSE
=0 ) which validates the reliability of the proposed QKDIE framework.
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.
This paper describes a novel steganography algorithm that combines quantum computing with the least significant bit technique (LSB). Using the quantum properties, along with the Python programming language and the Qiskit framework for the circuit simulation, a sub-image can be hidden inside a usual image. For a gray image, this article presents how the LSB of each of the first 16 pixels on the edges can be used to hide two threshold values, that are then used to filter out the image and reveal the secret message. The speedup, compared to the classical version, is possible due to the quantum representation of an image (NEQR is used in this paper) and the efficiency of the novel multi-bit quantum comparators.