A Hybrid Approach for Data Hiding using Twofish Algorithm and Compression Steganography Techniques

Abstract

Data compression and encryption are essential components of information security, facilitating efficient data handling, reduced storage requirements, and secure data transmission. The system presents a novel hybrid data compression algorithm that combines lossy and lossless compression techniques, along with Twofish cryptography. The hybrid approach leverages the strengths of different compression techniques. First, the Huffman coding algorithm is employed to compress textual data efficiently. Subsequently, the cover image undergoes lossy compression using the Discrete Wavelet Transform (DWT) technique. To fortify data security, the Twofish algorithm offers robust and high-level encryption. The encrypted data is then embedded into the compacted cover image using the least significant bit (LSB) technique in a steganographic manner. In the evaluation phase, the system's performance is assessed using key metrics, bits per pixel, mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM). Comparative analysis with existing methodologies demonstrates the superior performance and methodological efficiency of the system. The results indicate that the hybrid approach strikes a balance between compression efficiency and data security, enabling faster data transmission over limited bandwidth connections and effectively utilizing storage media.