Secure LSB Steganography Using Quantum Logistic Map–Based Pseudo-Random Sequences

Abstract

As digital communication increasingly moves onto untrusted networks, the need for truly secure and stealthy data hiding has become critical. This paper introduces a new LSB steganography method that's both low-distortion and high-security, with a clever trick at its core: it uses a Quantum Logistic Map (QLM) to generate its pseudo-random sequences. We chose the QLM because it offers a significantly stronger and more dynamic range of chaos than classical logistic models, all while remaining computationally lightweight enough for real-time applications. Here’s how it works: instead of embedding data in a predictable order, the QLM-derived sequence dictates the exact pixel locations and bit-modulation patterns, effectively scattering the hidden data across the image. This scattering is the key, as it erases the statistical footprints that steganalysis tools typically hunt for. Our experiments confirm this approach is a success: the method supports a high data payload with no noticeable visual degradation, backed by high PSNR, low MSE, and excellent SSIM scores (proving the image's structure remains intact). Statistically, it's a ghost; histogram analysis shows minimal deviation from the original, and pixel correlations remain natural, making it incredibly hard to detect. The system also proves to be robust (stable BER) and computationally efficient (low embedding/extraction times). In summary, by integrating the superior randomness of the QLM with an optimized LSB strategy, we've developed a balanced and practical solution that excels in imperceptibility, robustness, and security, making it a highly promising tool for modern secure communication.